From db395155b31b1d19408da32b0f47475815e5ec91 Mon Sep 17 00:00:00 2001 From: Ilya Lavrenov Date: Fri, 15 Sep 2023 06:53:32 +0400 Subject: [PATCH 01/12] Removed warnings suppressions for extra modukes (#16479) --- cmake/developer_package/frontends/frontends.cmake | 2 +- cmake/extra_modules.cmake | 6 ------ src/inference/tests/functional/CMakeLists.txt | 6 +++--- src/inference/tests/unit/CMakeLists.txt | 9 ++++----- src/plugins/intel_cpu/CMakeLists.txt | 1 + src/plugins/intel_gpu/src/graph/broadcast.cpp | 5 ++++- src/plugins/intel_gpu/src/graph/dft.cpp | 8 +++++++- .../src/graph/impls/onednn/reorder_onednn.cpp | 5 +++-- .../tests/functional/op_reference/reorg_yolo.cpp | 10 ++++++++++ 9 files changed, 33 insertions(+), 19 deletions(-) diff --git a/cmake/developer_package/frontends/frontends.cmake b/cmake/developer_package/frontends/frontends.cmake index c772ed706b7a5f..964dc6da443e81 100644 --- a/cmake/developer_package/frontends/frontends.cmake +++ b/cmake/developer_package/frontends/frontends.cmake @@ -228,7 +228,7 @@ macro(ov_add_frontend) # protobuf generated code emits -Wsuggest-override error if(SUGGEST_OVERRIDE_SUPPORTED) - target_compile_options(${TARGET_NAME} PRIVATE -Wno-suggest-override) + target_compile_options(${TARGET_NAME} PRIVATE $<$:-Wno-suggest-override>) endif() # install protobuf if it is not installed yet diff --git a/cmake/extra_modules.cmake b/cmake/extra_modules.cmake index c0a5e2288f5e82..afc1dc335b3e55 100644 --- a/cmake/extra_modules.cmake +++ b/cmake/extra_modules.cmake @@ -132,12 +132,6 @@ endif()\n") ov_dev_package_no_errors() ov_deprecated_no_errors() - if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC") - # 'argument': conversion from 'size_t' to 'int', possible loss of data - ov_add_compiler_flags(/wd4267) - ov_add_compiler_flags(/wd4244) - endif() - # add each extra module foreach(module_path IN LISTS extra_modules) if(module_path) diff --git a/src/inference/tests/functional/CMakeLists.txt b/src/inference/tests/functional/CMakeLists.txt index 8ebd3f806bdbc3..66f819df8e84d7 100644 --- a/src/inference/tests/functional/CMakeLists.txt +++ b/src/inference/tests/functional/CMakeLists.txt @@ -2,12 +2,12 @@ # SPDX-License-Identifier: Apache-2.0 # +set(TARGET_NAME ov_inference_functional_tests) + if(SUGGEST_OVERRIDE_SUPPORTED) - ov_add_compiler_flags(-Wno-suggest-override) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-suggest-override") endif() -set(TARGET_NAME ov_inference_functional_tests) - set(DEPENDENCIES mock_engine template_extension diff --git a/src/inference/tests/unit/CMakeLists.txt b/src/inference/tests/unit/CMakeLists.txt index 575623073a169c..9aff0e1adbe3b0 100644 --- a/src/inference/tests/unit/CMakeLists.txt +++ b/src/inference/tests/unit/CMakeLists.txt @@ -4,6 +4,10 @@ set(TARGET_NAME ov_inference_unit_tests) +if(SUGGEST_OVERRIDE_SUPPORTED) + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-suggest-override") +endif() + ov_add_test_target( NAME ${TARGET_NAME} ROOT ${CMAKE_CURRENT_SOURCE_DIR} @@ -15,8 +19,3 @@ ov_add_test_target( LABELS OV ) - -check_cxx_compiler_flag(-Wno-suggest-override SUPPORT_WNO_SUGGEST_OVERRIDE) -if(SUPPORT_WNO_SUGGEST_OVERRIDE) - ov_add_compiler_flags(-Wno-suggest-override) -endif() diff --git a/src/plugins/intel_cpu/CMakeLists.txt b/src/plugins/intel_cpu/CMakeLists.txt index b2a2e0fab32608..72784b793277c8 100644 --- a/src/plugins/intel_cpu/CMakeLists.txt +++ b/src/plugins/intel_cpu/CMakeLists.txt @@ -10,6 +10,7 @@ set(TARGET_NAME "openvino_intel_cpu_plugin") if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC") # C4267, 4244 issues from oneDNN headers conversion from 'XXX' to 'YYY', possible loss of data + ov_add_compiler_flags(/wd4018) ov_add_compiler_flags(/wd4267) ov_add_compiler_flags(/wd4244) # mkldnn headers: '<<': result of 32-bit shift implicitly converted to 64 bits diff --git a/src/plugins/intel_gpu/src/graph/broadcast.cpp b/src/plugins/intel_gpu/src/graph/broadcast.cpp index fdce54766b26dd..e4e5b369dabd0c 100644 --- a/src/plugins/intel_gpu/src/graph/broadcast.cpp +++ b/src/plugins/intel_gpu/src/graph/broadcast.cpp @@ -22,7 +22,10 @@ layout broadcast_inst::calc_output_layout(broadcast_node const& node, kernel_imp auto desc = impl_param.typed_desc(); if (!desc->target_shape.empty()) { - std::vector dims_converted(desc->target_shape.begin(), desc->target_shape.end()); + std::vector dims_converted(desc->target_shape.size()); + std::transform(desc->target_shape.begin(), desc->target_shape.end(), dims_converted.begin(), [](size_t value) { + return static_cast(value); + }); for (size_t i = dims_converted.size(); i < 4; i++) dims_converted.push_back(1); // extend shape to 4d diff --git a/src/plugins/intel_gpu/src/graph/dft.cpp b/src/plugins/intel_gpu/src/graph/dft.cpp index 406cce3374e911..6b52ff8403f3e6 100644 --- a/src/plugins/intel_gpu/src/graph/dft.cpp +++ b/src/plugins/intel_gpu/src/graph/dft.cpp @@ -14,7 +14,13 @@ layout dft_inst::calc_output_layout(const dft_node& node, const kernel_impl_para const auto primitive = impl_param.typed_desc(); const auto input_layout = impl_param.get_input_layout(); - std::vector dims_converted(primitive->output_shape.begin(), primitive->output_shape.end()); + std::vector dims_converted(primitive->output_shape.size()); + std::transform(primitive->output_shape.begin(), + primitive->output_shape.end(), + dims_converted.begin(), + [](size_t value) { + return static_cast(value); + }); // Extend shape to 4d by pushing ones at the end (needed to support less than 4d cases) for (auto i = dims_converted.size(); i < 4; ++i) { diff --git a/src/plugins/intel_gpu/src/graph/impls/onednn/reorder_onednn.cpp b/src/plugins/intel_gpu/src/graph/impls/onednn/reorder_onednn.cpp index 433e043067f9bf..97fdb612e89272 100644 --- a/src/plugins/intel_gpu/src/graph/impls/onednn/reorder_onednn.cpp +++ b/src/plugins/intel_gpu/src/graph/impls/onednn/reorder_onednn.cpp @@ -32,8 +32,9 @@ struct reorder_onednn : typed_primitive_onednn_impl(i))); + args.insert({input_idx++, input.get_onednn_memory(_pd.dnnl::primitive_desc_base::src_desc(static_cast(i)), offset)}); } { 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 5e8f713425ec94..ddea9ce114b6f5 100644 --- a/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp +++ b/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp @@ -11,6 +11,12 @@ using namespace reference_tests; using namespace ov; namespace { + +#ifdef _MSC_VER +# pragma warning(push) +# pragma warning(disable : 4244) +#endif + struct ReorgYoloParams { template ReorgYoloParams(const ov::Strides& stride, @@ -38,6 +44,10 @@ struct ReorgYoloParams { std::string testcaseName; }; +#ifdef _MSC_VER +# pragma warning(pop) +#endif + class ReferenceReorgYoloLayerTest : public testing::TestWithParam, public CommonReferenceTest { public: void SetUp() override { From 545779f99fe5ebf55faa832b4a649054807d1777 Mon Sep 17 00:00:00 2001 From: Karol Blaszczak Date: Fri, 15 Sep 2023 08:07:53 +0200 Subject: [PATCH 02/12] [DOCS] troubleshooting article --- docs/install_guides/troubleshooting.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/docs/install_guides/troubleshooting.md b/docs/install_guides/troubleshooting.md index e1a6d03be41216..d5c969bee40108 100644 --- a/docs/install_guides/troubleshooting.md +++ b/docs/install_guides/troubleshooting.md @@ -10,7 +10,12 @@ .. _troubleshooting guide for install: -This guide provides general troubleshooting steps and solutions to possible issues that can be encountered while installing and configuring OpenVINO™. +| This guide provides general troubleshooting steps and solutions to possible issues that + may be encountered while installing and configuring OpenVINO™. For a comprehensive + database of support topics on OpenVINO, go to: +| `Support for OpenVINO™ toolkit `__ + + .. _install_for_prc: From ceab8059d10614a3520f3a58ebb25249614a050e Mon Sep 17 00:00:00 2001 From: Zhang Yi Date: Fri, 15 Sep 2023 14:17:45 +0800 Subject: [PATCH 03/12] [CPU]apply sdl requirement (#19438) --- licensing/runtime-third-party-programs.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/licensing/runtime-third-party-programs.txt b/licensing/runtime-third-party-programs.txt index 7180cd9f63e92c..1ce84ec219b6ea 100644 --- a/licensing/runtime-third-party-programs.txt +++ b/licensing/runtime-third-party-programs.txt @@ -1641,7 +1641,7 @@ SOFTWARE. ------------------------------------------------------------- -24. MLAS (https://github.com/microsoft/onnxruntime) +24. Microsoft onnxruntime (https://github.com/microsoft/onnxruntime) MIT License From 619c4bfce1dad7e7abe6fd46c058160ac28b9ca2 Mon Sep 17 00:00:00 2001 From: Ilya Lavrenov Date: Fri, 15 Sep 2023 10:19:34 +0400 Subject: [PATCH 04/12] Enable tests for Conan ARM build (#19860) --- .ci/azure/linux_arm64.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.ci/azure/linux_arm64.yml b/.ci/azure/linux_arm64.yml index ecde288fc439fe..618af65e537ea2 100644 --- a/.ci/azure/linux_arm64.yml +++ b/.ci/azure/linux_arm64.yml @@ -183,7 +183,6 @@ jobs: - script: | set -e source $(BUILD_OPENVINO)/dependencies/conanbuild.sh - # TODO: return tests building once GPU plugin migrates to Plugin API 2.0 cmake \ -DCMAKE_VERBOSE_MAKEFILE=ON \ -DBUILD_SHARED_LIBS=OFF \ @@ -197,6 +196,7 @@ jobs: -DPYTHON_LIBRARY=/usr/lib/aarch64-linux-gnu/libc-2.31.so \ -DPYTHON_INCLUDE_DIR=$(Agent.ToolsDirectory)/Python/$(OV_PYTHON_VERSION)/x64/include/python$(OV_PYTHON_VERSION_MAJOR_MINOR) \ -DENABLE_DATA=OFF \ + -DENABLE_TESTS=ON \ -DENABLE_SYSTEM_TBB=ON \ -DENABLE_SYSTEM_PROTOBUF=ON \ -DENABLE_SYSTEM_SNAPPY=ON \ From d62348337fe3a5af2cab66dd38778cc07b6291d6 Mon Sep 17 00:00:00 2001 From: Anastasia Kuporosova Date: Fri, 15 Sep 2023 10:17:44 +0200 Subject: [PATCH 05/12] [PyOV] Import properties from openvino (#19815) --- .../src/openvino/properties/__init__.py | 36 ++ .../openvino/properties/device/__init__.py | 22 ++ .../src/openvino/properties/hint/__init__.py | 21 + .../properties/intel_auto/__init__.py | 7 + .../openvino/properties/intel_cpu/__init__.py | 6 + .../openvino/properties/intel_gpu/__init__.py | 15 + .../properties/intel_gpu/hint/__init__.py | 12 + .../src/openvino/properties/log/__init__.py | 9 + .../openvino/properties/streams/__init__.py | 9 + .../tests/test_runtime/test_properties.py | 373 +++++++++--------- 10 files changed, 328 insertions(+), 182 deletions(-) create mode 100644 src/bindings/python/src/openvino/properties/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/device/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/hint/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/intel_auto/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/intel_cpu/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/intel_gpu/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/intel_gpu/hint/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/log/__init__.py create mode 100644 src/bindings/python/src/openvino/properties/streams/__init__.py diff --git a/src/bindings/python/src/openvino/properties/__init__.py b/src/bindings/python/src/openvino/properties/__init__.py new file mode 100644 index 00000000000000..a9fa5a0dac4e93 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/__init__.py @@ -0,0 +1,36 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Enums +from openvino._pyopenvino.properties import Affinity + +# Properties +from openvino._pyopenvino.properties import enable_profiling +from openvino._pyopenvino.properties import cache_dir +from openvino._pyopenvino.properties import auto_batch_timeout +from openvino._pyopenvino.properties import num_streams +from openvino._pyopenvino.properties import inference_num_threads +from openvino._pyopenvino.properties import compilation_num_threads +from openvino._pyopenvino.properties import affinity +from openvino._pyopenvino.properties import force_tbb_terminate +from openvino._pyopenvino.properties import enable_mmap +from openvino._pyopenvino.properties import supported_properties +from openvino._pyopenvino.properties import available_devices +from openvino._pyopenvino.properties import model_name +from openvino._pyopenvino.properties import optimal_number_of_infer_requests +from openvino._pyopenvino.properties import range_for_streams +from openvino._pyopenvino.properties import optimal_batch_size +from openvino._pyopenvino.properties import max_batch_size +from openvino._pyopenvino.properties import range_for_async_infer_requests +from openvino._pyopenvino.properties import execution_devices +from openvino._pyopenvino.properties import loaded_from_cache + +# Submodules +from openvino.runtime.properties import hint +from openvino.runtime.properties import intel_cpu +from openvino.runtime.properties import intel_gpu +from openvino.runtime.properties import intel_auto +from openvino.runtime.properties import device +from openvino.runtime.properties import log +from openvino.runtime.properties import streams diff --git a/src/bindings/python/src/openvino/properties/device/__init__.py b/src/bindings/python/src/openvino/properties/device/__init__.py new file mode 100644 index 00000000000000..5729dd101234f3 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/device/__init__.py @@ -0,0 +1,22 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Enums +from openvino._pyopenvino.properties.device import Type + +# Properties +from openvino._pyopenvino.properties.device import priorities +from openvino._pyopenvino.properties.device import id +from openvino._pyopenvino.properties.device import full_name +from openvino._pyopenvino.properties.device import architecture +from openvino._pyopenvino.properties.device import type +from openvino._pyopenvino.properties.device import gops +from openvino._pyopenvino.properties.device import thermal +from openvino._pyopenvino.properties.device import capabilities +from openvino._pyopenvino.properties.device import uuid +from openvino._pyopenvino.properties.device import luid +from openvino._pyopenvino.properties.device import properties + +# Classes +from openvino._pyopenvino.properties.device import Capability diff --git a/src/bindings/python/src/openvino/properties/hint/__init__.py b/src/bindings/python/src/openvino/properties/hint/__init__.py new file mode 100644 index 00000000000000..9b4fdd0d752f8a --- /dev/null +++ b/src/bindings/python/src/openvino/properties/hint/__init__.py @@ -0,0 +1,21 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Enums +from openvino._pyopenvino.properties.hint import Priority +from openvino._pyopenvino.properties.hint import SchedulingCoreType +from openvino._pyopenvino.properties.hint import ExecutionMode +from openvino.runtime.properties.hint.overloads import PerformanceMode + +# Properties +from openvino._pyopenvino.properties.hint import inference_precision +from openvino._pyopenvino.properties.hint import model_priority +from openvino._pyopenvino.properties.hint import performance_mode +from openvino._pyopenvino.properties.hint import enable_cpu_pinning +from openvino._pyopenvino.properties.hint import scheduling_core_type +from openvino._pyopenvino.properties.hint import enable_hyper_threading +from openvino._pyopenvino.properties.hint import execution_mode +from openvino._pyopenvino.properties.hint import num_requests +from openvino._pyopenvino.properties.hint import model +from openvino._pyopenvino.properties.hint import allow_auto_batching diff --git a/src/bindings/python/src/openvino/properties/intel_auto/__init__.py b/src/bindings/python/src/openvino/properties/intel_auto/__init__.py new file mode 100644 index 00000000000000..a9a7e450794638 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/intel_auto/__init__.py @@ -0,0 +1,7 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +from openvino._pyopenvino.properties.intel_auto import device_bind_buffer +from openvino._pyopenvino.properties.intel_auto import enable_startup_fallback +from openvino._pyopenvino.properties.intel_auto import enable_runtime_fallback diff --git a/src/bindings/python/src/openvino/properties/intel_cpu/__init__.py b/src/bindings/python/src/openvino/properties/intel_cpu/__init__.py new file mode 100644 index 00000000000000..2b947dc960e809 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/intel_cpu/__init__.py @@ -0,0 +1,6 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +from openvino._pyopenvino.properties.intel_cpu import denormals_optimization +from openvino._pyopenvino.properties.intel_cpu import sparse_weights_decompression_rate diff --git a/src/bindings/python/src/openvino/properties/intel_gpu/__init__.py b/src/bindings/python/src/openvino/properties/intel_gpu/__init__.py new file mode 100644 index 00000000000000..0cfa6dde23d7e3 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/intel_gpu/__init__.py @@ -0,0 +1,15 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Properties +from openvino._pyopenvino.properties.intel_gpu import device_total_mem_size +from openvino._pyopenvino.properties.intel_gpu import uarch_version +from openvino._pyopenvino.properties.intel_gpu import execution_units_count +from openvino._pyopenvino.properties.intel_gpu import memory_statistics +from openvino._pyopenvino.properties.intel_gpu import enable_loop_unrolling +from openvino._pyopenvino.properties.intel_gpu import disable_winograd_convolution + +# Classes +from openvino._pyopenvino.properties.intel_gpu import MemoryType +from openvino._pyopenvino.properties.intel_gpu import CapabilityGPU diff --git a/src/bindings/python/src/openvino/properties/intel_gpu/hint/__init__.py b/src/bindings/python/src/openvino/properties/intel_gpu/hint/__init__.py new file mode 100644 index 00000000000000..78b18bdf477be5 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/intel_gpu/hint/__init__.py @@ -0,0 +1,12 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Properties +from openvino._pyopenvino.properties.intel_gpu.hint import queue_throttle +from openvino._pyopenvino.properties.intel_gpu.hint import queue_priority +from openvino._pyopenvino.properties.intel_gpu.hint import host_task_priority +from openvino._pyopenvino.properties.intel_gpu.hint import available_device_mem + +# Classes +from openvino._pyopenvino.properties.intel_gpu.hint import ThrottleLevel diff --git a/src/bindings/python/src/openvino/properties/log/__init__.py b/src/bindings/python/src/openvino/properties/log/__init__.py new file mode 100644 index 00000000000000..bf29a7a70e71ac --- /dev/null +++ b/src/bindings/python/src/openvino/properties/log/__init__.py @@ -0,0 +1,9 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Enums +from openvino._pyopenvino.properties.log import Level + +# Properties +from openvino._pyopenvino.properties.log import level diff --git a/src/bindings/python/src/openvino/properties/streams/__init__.py b/src/bindings/python/src/openvino/properties/streams/__init__.py new file mode 100644 index 00000000000000..e1ce0b19044f57 --- /dev/null +++ b/src/bindings/python/src/openvino/properties/streams/__init__.py @@ -0,0 +1,9 @@ +# -*- coding: utf-8 -*- +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Properties +from openvino._pyopenvino.properties.streams import num + +# Classes +from openvino._pyopenvino.properties.streams import Num diff --git a/src/bindings/python/tests/test_runtime/test_properties.py b/src/bindings/python/tests/test_runtime/test_properties.py index ae1b4c908e7ee5..e11afaf5a844c7 100644 --- a/src/bindings/python/tests/test_runtime/test_properties.py +++ b/src/bindings/python/tests/test_runtime/test_properties.py @@ -6,7 +6,16 @@ import numpy as np import os -from openvino import Core, Type, OVAny, properties +import openvino.properties as props +import openvino.properties.hint as hints +import openvino.properties.intel_cpu as intel_cpu +import openvino.properties.intel_auto as intel_auto +import openvino.properties.intel_gpu as intel_gpu +import openvino.properties.intel_gpu.hint as intel_gpu_hint +import openvino.properties.device as device +import openvino.properties.log as log +import openvino.properties.streams as streams +from openvino import Core, Type, OVAny ### @@ -14,22 +23,22 @@ ### def test_properties_ro_base(): with pytest.raises(TypeError) as e: - properties.supported_properties("something") + props.supported_properties("something") assert "incompatible function arguments" in str(e.value) def test_properties_rw_base(): - assert properties.cache_dir() == "CACHE_DIR" - assert properties.cache_dir("./test_dir") == ("CACHE_DIR", OVAny("./test_dir")) + assert props.cache_dir() == "CACHE_DIR" + assert props.cache_dir("./test_dir") == ("CACHE_DIR", OVAny("./test_dir")) with pytest.raises(TypeError) as e: - properties.cache_dir(6) + props.cache_dir(6) assert "incompatible function arguments" in str(e.value) def test_deprecation(): with pytest.warns(DeprecationWarning) as w: - _ = properties.hint.PerformanceMode.UNDEFINED + _ = hints.PerformanceMode.UNDEFINED assert issubclass(w[0].category, DeprecationWarning) assert "PerformanceMode.UNDEFINED is deprecated and will be removed" in str(w[0].message) @@ -41,63 +50,63 @@ def test_deprecation(): ("ov_enum", "expected_values"), [ ( - properties.Affinity, + props.Affinity, ( - (properties.Affinity.NONE, "Affinity.NONE", -1), - (properties.Affinity.CORE, "Affinity.CORE", 0), - (properties.Affinity.NUMA, "Affinity.NUMA", 1), - (properties.Affinity.HYBRID_AWARE, "Affinity.HYBRID_AWARE", 2), + (props.Affinity.NONE, "Affinity.NONE", -1), + (props.Affinity.CORE, "Affinity.CORE", 0), + (props.Affinity.NUMA, "Affinity.NUMA", 1), + (props.Affinity.HYBRID_AWARE, "Affinity.HYBRID_AWARE", 2), ), ), ( - properties.hint.Priority, + hints.Priority, ( - (properties.hint.Priority.LOW, "Priority.LOW", 0), - (properties.hint.Priority.MEDIUM, "Priority.MEDIUM", 1), - (properties.hint.Priority.HIGH, "Priority.HIGH", 2), - (properties.hint.Priority.DEFAULT, "Priority.MEDIUM", 1), + (hints.Priority.LOW, "Priority.LOW", 0), + (hints.Priority.MEDIUM, "Priority.MEDIUM", 1), + (hints.Priority.HIGH, "Priority.HIGH", 2), + (hints.Priority.DEFAULT, "Priority.MEDIUM", 1), ), ), ( - properties.hint.PerformanceMode, + hints.PerformanceMode, ( - (properties.hint.PerformanceMode.UNDEFINED, "PerformanceMode.UNDEFINED", -1), - (properties.hint.PerformanceMode.LATENCY, "PerformanceMode.LATENCY", 1), - (properties.hint.PerformanceMode.THROUGHPUT, "PerformanceMode.THROUGHPUT", 2), - (properties.hint.PerformanceMode.CUMULATIVE_THROUGHPUT, "PerformanceMode.CUMULATIVE_THROUGHPUT", 3), + (hints.PerformanceMode.UNDEFINED, "PerformanceMode.UNDEFINED", -1), + (hints.PerformanceMode.LATENCY, "PerformanceMode.LATENCY", 1), + (hints.PerformanceMode.THROUGHPUT, "PerformanceMode.THROUGHPUT", 2), + (hints.PerformanceMode.CUMULATIVE_THROUGHPUT, "PerformanceMode.CUMULATIVE_THROUGHPUT", 3), ), ), ( - properties.hint.SchedulingCoreType, + hints.SchedulingCoreType, ( - (properties.hint.SchedulingCoreType.ANY_CORE, "SchedulingCoreType.ANY_CORE", 0), - (properties.hint.SchedulingCoreType.PCORE_ONLY, "SchedulingCoreType.PCORE_ONLY", 1), - (properties.hint.SchedulingCoreType.ECORE_ONLY, "SchedulingCoreType.ECORE_ONLY", 2), + (hints.SchedulingCoreType.ANY_CORE, "SchedulingCoreType.ANY_CORE", 0), + (hints.SchedulingCoreType.PCORE_ONLY, "SchedulingCoreType.PCORE_ONLY", 1), + (hints.SchedulingCoreType.ECORE_ONLY, "SchedulingCoreType.ECORE_ONLY", 2), ), ), ( - properties.hint.ExecutionMode, + hints.ExecutionMode, ( - (properties.hint.ExecutionMode.PERFORMANCE, "ExecutionMode.PERFORMANCE", 1), - (properties.hint.ExecutionMode.ACCURACY, "ExecutionMode.ACCURACY", 2), + (hints.ExecutionMode.PERFORMANCE, "ExecutionMode.PERFORMANCE", 1), + (hints.ExecutionMode.ACCURACY, "ExecutionMode.ACCURACY", 2), ), ), ( - properties.device.Type, + device.Type, ( - (properties.device.Type.INTEGRATED, "Type.INTEGRATED", 0), - (properties.device.Type.DISCRETE, "Type.DISCRETE", 1), + (device.Type.INTEGRATED, "Type.INTEGRATED", 0), + (device.Type.DISCRETE, "Type.DISCRETE", 1), ), ), ( - properties.log.Level, + log.Level, ( - (properties.log.Level.NO, "Level.NO", -1), - (properties.log.Level.ERR, "Level.ERR", 0), - (properties.log.Level.WARNING, "Level.WARNING", 1), - (properties.log.Level.INFO, "Level.INFO", 2), - (properties.log.Level.DEBUG, "Level.DEBUG", 3), - (properties.log.Level.TRACE, "Level.TRACE", 4), + (log.Level.NO, "Level.NO", -1), + (log.Level.ERR, "Level.ERR", 0), + (log.Level.WARNING, "Level.WARNING", 1), + (log.Level.INFO, "Level.INFO", 2), + (log.Level.DEBUG, "Level.DEBUG", 3), + (log.Level.TRACE, "Level.TRACE", 4), ), ), ], @@ -117,10 +126,10 @@ def test_properties_enums(ov_enum, expected_values): [ ( ( - properties.intel_gpu.hint.ThrottleLevel.LOW, - properties.intel_gpu.hint.ThrottleLevel.MEDIUM, - properties.intel_gpu.hint.ThrottleLevel.HIGH, - properties.intel_gpu.hint.ThrottleLevel.DEFAULT, + intel_gpu_hint.ThrottleLevel.LOW, + intel_gpu_hint.ThrottleLevel.MEDIUM, + intel_gpu_hint.ThrottleLevel.HIGH, + intel_gpu_hint.ThrottleLevel.DEFAULT, ), ( ("Priority.LOW", 0), @@ -145,28 +154,28 @@ def test_conflicting_enum(proxy_enums, expected_values): @pytest.mark.parametrize( ("ov_property_ro", "expected_value"), [ - (properties.supported_properties, "SUPPORTED_PROPERTIES"), - (properties.available_devices, "AVAILABLE_DEVICES"), - (properties.model_name, "NETWORK_NAME"), - (properties.optimal_number_of_infer_requests, "OPTIMAL_NUMBER_OF_INFER_REQUESTS"), - (properties.range_for_streams, "RANGE_FOR_STREAMS"), - (properties.optimal_batch_size, "OPTIMAL_BATCH_SIZE"), - (properties.max_batch_size, "MAX_BATCH_SIZE"), - (properties.range_for_async_infer_requests, "RANGE_FOR_ASYNC_INFER_REQUESTS"), - (properties.execution_devices, "EXECUTION_DEVICES"), - (properties.loaded_from_cache, "LOADED_FROM_CACHE"), - (properties.device.full_name, "FULL_DEVICE_NAME"), - (properties.device.architecture, "DEVICE_ARCHITECTURE"), - (properties.device.type, "DEVICE_TYPE"), - (properties.device.gops, "DEVICE_GOPS"), - (properties.device.thermal, "DEVICE_THERMAL"), - (properties.device.uuid, "DEVICE_UUID"), - (properties.device.luid, "DEVICE_LUID"), - (properties.device.capabilities, "OPTIMIZATION_CAPABILITIES"), - (properties.intel_gpu.device_total_mem_size, "GPU_DEVICE_TOTAL_MEM_SIZE"), - (properties.intel_gpu.uarch_version, "GPU_UARCH_VERSION"), - (properties.intel_gpu.execution_units_count, "GPU_EXECUTION_UNITS_COUNT"), - (properties.intel_gpu.memory_statistics, "GPU_MEMORY_STATISTICS"), + (props.supported_properties, "SUPPORTED_PROPERTIES"), + (props.available_devices, "AVAILABLE_DEVICES"), + (props.model_name, "NETWORK_NAME"), + (props.optimal_number_of_infer_requests, "OPTIMAL_NUMBER_OF_INFER_REQUESTS"), + (props.range_for_streams, "RANGE_FOR_STREAMS"), + (props.optimal_batch_size, "OPTIMAL_BATCH_SIZE"), + (props.max_batch_size, "MAX_BATCH_SIZE"), + (props.range_for_async_infer_requests, "RANGE_FOR_ASYNC_INFER_REQUESTS"), + (props.execution_devices, "EXECUTION_DEVICES"), + (props.loaded_from_cache, "LOADED_FROM_CACHE"), + (device.full_name, "FULL_DEVICE_NAME"), + (device.architecture, "DEVICE_ARCHITECTURE"), + (device.type, "DEVICE_TYPE"), + (device.gops, "DEVICE_GOPS"), + (device.thermal, "DEVICE_THERMAL"), + (device.uuid, "DEVICE_UUID"), + (device.luid, "DEVICE_LUID"), + (device.capabilities, "OPTIMIZATION_CAPABILITIES"), + (intel_gpu.device_total_mem_size, "GPU_DEVICE_TOTAL_MEM_SIZE"), + (intel_gpu.uarch_version, "GPU_UARCH_VERSION"), + (intel_gpu.execution_units_count, "GPU_EXECUTION_UNITS_COUNT"), + (intel_gpu.memory_statistics, "GPU_MEMORY_STATISTICS"), ], ) def test_properties_ro(ov_property_ro, expected_value): @@ -181,7 +190,7 @@ def test_properties_ro(ov_property_ro, expected_value): ("ov_property_rw", "expected_value", "test_values"), [ ( - properties.enable_profiling, + props.enable_profiling, "PERF_COUNT", ( (True, True), @@ -191,12 +200,12 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.cache_dir, + props.cache_dir, "CACHE_DIR", (("./test_cache", "./test_cache"),), ), ( - properties.auto_batch_timeout, + props.auto_batch_timeout, "AUTO_BATCH_TIMEOUT", ( (21, 21), @@ -206,7 +215,7 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.inference_num_threads, + props.inference_num_threads, "INFERENCE_NUM_THREADS", ( (-8, -8), @@ -214,30 +223,30 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.compilation_num_threads, + props.compilation_num_threads, "COMPILATION_NUM_THREADS", ((44, 44),), ), ( - properties.affinity, + props.affinity, "AFFINITY", - ((properties.Affinity.NONE, properties.Affinity.NONE),), + ((props.Affinity.NONE, props.Affinity.NONE),), ), - (properties.force_tbb_terminate, "FORCE_TBB_TERMINATE", ((True, True), (False, False))), - (properties.enable_mmap, "ENABLE_MMAP", ((True, True), (False, False))), - (properties.hint.inference_precision, "INFERENCE_PRECISION_HINT", ((Type.f32, Type.f32),)), + (props.force_tbb_terminate, "FORCE_TBB_TERMINATE", ((True, True), (False, False))), + (props.enable_mmap, "ENABLE_MMAP", ((True, True), (False, False))), + (hints.inference_precision, "INFERENCE_PRECISION_HINT", ((Type.f32, Type.f32),)), ( - properties.hint.model_priority, + hints.model_priority, "MODEL_PRIORITY", - ((properties.hint.Priority.LOW, properties.hint.Priority.LOW),), + ((hints.Priority.LOW, hints.Priority.LOW),), ), ( - properties.hint.performance_mode, + hints.performance_mode, "PERFORMANCE_HINT", - ((properties.hint.PerformanceMode.UNDEFINED, properties.hint.PerformanceMode.UNDEFINED),), + ((hints.PerformanceMode.UNDEFINED, hints.PerformanceMode.UNDEFINED),), ), ( - properties.hint.enable_cpu_pinning, + hints.enable_cpu_pinning, "ENABLE_CPU_PINNING", ( (True, True), @@ -247,12 +256,12 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.hint.scheduling_core_type, + hints.scheduling_core_type, "SCHEDULING_CORE_TYPE", - ((properties.hint.SchedulingCoreType.PCORE_ONLY, properties.hint.SchedulingCoreType.PCORE_ONLY),), + ((hints.SchedulingCoreType.PCORE_ONLY, hints.SchedulingCoreType.PCORE_ONLY),), ), ( - properties.hint.enable_hyper_threading, + hints.enable_hyper_threading, "ENABLE_HYPER_THREADING", ( (True, True), @@ -262,27 +271,27 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.hint.execution_mode, + hints.execution_mode, "EXECUTION_MODE_HINT", - ((properties.hint.ExecutionMode.PERFORMANCE, properties.hint.ExecutionMode.PERFORMANCE),), + ((hints.ExecutionMode.PERFORMANCE, hints.ExecutionMode.PERFORMANCE),), ), ( - properties.hint.num_requests, + hints.num_requests, "PERFORMANCE_HINT_NUM_REQUESTS", ((8, 8),), ), ( - properties.hint.allow_auto_batching, + hints.allow_auto_batching, "ALLOW_AUTO_BATCHING", ((True, True),), ), ( - properties.intel_cpu.denormals_optimization, + intel_cpu.denormals_optimization, "CPU_DENORMALS_OPTIMIZATION", ((True, True),), ), ( - properties.intel_cpu.sparse_weights_decompression_rate, + intel_cpu.sparse_weights_decompression_rate, "CPU_SPARSE_WEIGHTS_DECOMPRESSION_RATE", ( (0.1, np.float32(0.1)), @@ -290,7 +299,7 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.intel_auto.device_bind_buffer, + intel_auto.device_bind_buffer, "DEVICE_BIND_BUFFER", ( (True, True), @@ -300,7 +309,7 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.intel_auto.enable_startup_fallback, + intel_auto.enable_startup_fallback, "ENABLE_STARTUP_FALLBACK", ( (True, True), @@ -310,7 +319,7 @@ def test_properties_ro(ov_property_ro, expected_value): ), ), ( - properties.intel_auto.enable_runtime_fallback, + intel_auto.enable_runtime_fallback, "ENABLE_RUNTIME_FALLBACK", ( (True, True), @@ -319,39 +328,39 @@ def test_properties_ro(ov_property_ro, expected_value): (0, False), ), ), - (properties.device.id, "DEVICE_ID", (("0", "0"),)), + (device.id, "DEVICE_ID", (("0", "0"),)), ( - properties.log.level, + log.level, "LOG_LEVEL", - ((properties.log.Level.NO, properties.log.Level.NO),), + ((log.Level.NO, log.Level.NO),), ), ( - properties.intel_gpu.enable_loop_unrolling, + intel_gpu.enable_loop_unrolling, "GPU_ENABLE_LOOP_UNROLLING", ((True, True),), ), ( - properties.intel_gpu.disable_winograd_convolution, + intel_gpu.disable_winograd_convolution, "GPU_DISABLE_WINOGRAD_CONVOLUTION", ((True, True),), ), ( - properties.intel_gpu.hint.queue_throttle, + intel_gpu_hint.queue_throttle, "GPU_QUEUE_THROTTLE", - ((properties.intel_gpu.hint.ThrottleLevel.LOW, properties.hint.Priority.LOW),), + ((intel_gpu_hint.ThrottleLevel.LOW, hints.Priority.LOW),), ), ( - properties.intel_gpu.hint.queue_priority, + intel_gpu_hint.queue_priority, "GPU_QUEUE_PRIORITY", - ((properties.hint.Priority.LOW, properties.hint.Priority.LOW),), + ((hints.Priority.LOW, hints.Priority.LOW),), ), ( - properties.intel_gpu.hint.host_task_priority, + intel_gpu_hint.host_task_priority, "GPU_HOST_TASK_PRIORITY", - ((properties.hint.Priority.LOW, properties.hint.Priority.LOW),), + ((hints.Priority.LOW, hints.Priority.LOW),), ), ( - properties.intel_gpu.hint.available_device_mem, + intel_gpu_hint.available_device_mem, "AVAILABLE_DEVICE_MEM_SIZE", ((128, 128),), ), @@ -372,74 +381,74 @@ def test_properties_rw(ov_property_rw, expected_value, test_values): # Special cases ### def test_properties_device_priorities(): - assert properties.device.priorities() == "MULTI_DEVICE_PRIORITIES" - assert properties.device.priorities("CPU,GPU") == ("MULTI_DEVICE_PRIORITIES", OVAny("CPU,GPU,")) - assert properties.device.priorities("CPU", "GPU") == ("MULTI_DEVICE_PRIORITIES", OVAny("CPU,GPU,")) + assert device.priorities() == "MULTI_DEVICE_PRIORITIES" + assert device.priorities("CPU,GPU") == ("MULTI_DEVICE_PRIORITIES", OVAny("CPU,GPU,")) + assert device.priorities("CPU", "GPU") == ("MULTI_DEVICE_PRIORITIES", OVAny("CPU,GPU,")) with pytest.raises(TypeError) as e: value = 6 - properties.device.priorities("CPU", value) + device.priorities("CPU", value) assert f"Incorrect passed value: {value} , expected string values." in str(e.value) def test_properties_device_properties(): - assert properties.device.properties() == "DEVICE_PROPERTIES" + assert device.properties() == "DEVICE_PROPERTIES" def make_dict(*arg): return dict( # noqa: C406 [*arg]) def check(value1, value2): - assert properties.device.properties(value1) == ("DEVICE_PROPERTIES", OVAny(value2)) + assert device.properties(value1) == ("DEVICE_PROPERTIES", OVAny(value2)) - check({"CPU": {properties.streams.num(): 2}}, + check({"CPU": {streams.num(): 2}}, {"CPU": {"NUM_STREAMS": 2}}) - check({"CPU": make_dict(properties.streams.num(2))}, - {"CPU": {"NUM_STREAMS": properties.streams.Num(2)}}) - check({"GPU": make_dict(properties.hint.inference_precision(Type.f32))}, + check({"CPU": make_dict(streams.num(2))}, + {"CPU": {"NUM_STREAMS": streams.Num(2)}}) + check({"GPU": make_dict(hints.inference_precision(Type.f32))}, {"GPU": {"INFERENCE_PRECISION_HINT": Type.f32}}) - check({"CPU": make_dict(properties.streams.num(2), properties.hint.inference_precision(Type.f32))}, - {"CPU": {"INFERENCE_PRECISION_HINT": Type.f32, "NUM_STREAMS": properties.streams.Num(2)}}) - check({"CPU": make_dict(properties.streams.num(2), properties.hint.inference_precision(Type.f32)), - "GPU": make_dict(properties.streams.num(1), properties.hint.inference_precision(Type.f16))}, - {"CPU": {"INFERENCE_PRECISION_HINT": Type.f32, "NUM_STREAMS": properties.streams.Num(2)}, - "GPU": {"INFERENCE_PRECISION_HINT": Type.f16, "NUM_STREAMS": properties.streams.Num(1)}}) + check({"CPU": make_dict(streams.num(2), hints.inference_precision(Type.f32))}, + {"CPU": {"INFERENCE_PRECISION_HINT": Type.f32, "NUM_STREAMS": streams.Num(2)}}) + check({"CPU": make_dict(streams.num(2), hints.inference_precision(Type.f32)), + "GPU": make_dict(streams.num(1), hints.inference_precision(Type.f16))}, + {"CPU": {"INFERENCE_PRECISION_HINT": Type.f32, "NUM_STREAMS": streams.Num(2)}, + "GPU": {"INFERENCE_PRECISION_HINT": Type.f16, "NUM_STREAMS": streams.Num(1)}}) def test_properties_streams(): # Test extra Num class - assert properties.streams.Num().to_integer() == -1 - assert properties.streams.Num(2).to_integer() == 2 - assert properties.streams.Num.AUTO.to_integer() == -1 - assert properties.streams.Num.NUMA.to_integer() == -2 + assert streams.Num().to_integer() == -1 + assert streams.Num(2).to_integer() == 2 + assert streams.Num.AUTO.to_integer() == -1 + assert streams.Num.NUMA.to_integer() == -2 # Test RW property - property_tuple = properties.streams.num(properties.streams.Num.AUTO) + property_tuple = streams.num(streams.Num.AUTO) assert property_tuple[0] == "NUM_STREAMS" assert property_tuple[1].value == -1 - property_tuple = properties.streams.num(42) + property_tuple = streams.num(42) assert property_tuple[0] == "NUM_STREAMS" assert property_tuple[1].value == 42 def test_properties_capability(): - assert properties.device.Capability.FP32 == "FP32" - assert properties.device.Capability.BF16 == "BF16" - assert properties.device.Capability.FP16 == "FP16" - assert properties.device.Capability.INT8 == "INT8" - assert properties.device.Capability.INT16 == "INT16" - assert properties.device.Capability.BIN == "BIN" - assert properties.device.Capability.WINOGRAD == "WINOGRAD" - assert properties.device.Capability.EXPORT_IMPORT == "EXPORT_IMPORT" + assert device.Capability.FP32 == "FP32" + assert device.Capability.BF16 == "BF16" + assert device.Capability.FP16 == "FP16" + assert device.Capability.INT8 == "INT8" + assert device.Capability.INT16 == "INT16" + assert device.Capability.BIN == "BIN" + assert device.Capability.WINOGRAD == "WINOGRAD" + assert device.Capability.EXPORT_IMPORT == "EXPORT_IMPORT" def test_properties_memory_type_gpu(): - assert properties.intel_gpu.MemoryType.surface == "GPU_SURFACE" - assert properties.intel_gpu.MemoryType.buffer == "GPU_BUFFER" + assert intel_gpu.MemoryType.surface == "GPU_SURFACE" + assert intel_gpu.MemoryType.buffer == "GPU_BUFFER" def test_properties_capability_gpu(): - assert properties.intel_gpu.CapabilityGPU.HW_MATMUL == "GPU_HW_MATMUL" + assert intel_gpu.CapabilityGPU.HW_MATMUL == "GPU_HW_MATMUL" def test_properties_hint_model(): @@ -448,19 +457,19 @@ def test_properties_hint_model(): model = generate_add_model() - assert properties.hint.model() == "MODEL_PTR" + assert hints.model() == "MODEL_PTR" - property_tuple = properties.hint.model(model) + property_tuple = hints.model(model) assert property_tuple[0] == "MODEL_PTR" def test_single_property_setting(device): core = Core() - core.set_property(device, properties.streams.num(properties.streams.Num.AUTO)) + core.set_property(device, streams.num(streams.Num.AUTO)) - assert properties.streams.Num.AUTO.to_integer() == -1 - assert type(core.get_property(device, properties.streams.num())) == int + assert streams.Num.AUTO.to_integer() == -1 + assert type(core.get_property(device, streams.num())) == int @pytest.mark.skipif(os.environ.get("TEST_DEVICE", "CPU") != "CPU", reason=f"Cannot run test on device {os.environ.get('TEST_DEVICE')}, Plugin specific test") @@ -470,44 +479,44 @@ def test_single_property_setting(device): # Dict from list of tuples dict( # noqa: C406 [ # noqa: C406 - properties.enable_profiling(True), - properties.cache_dir("./"), - properties.inference_num_threads(9), - properties.affinity(properties.Affinity.NONE), - properties.hint.inference_precision(Type.f32), - properties.hint.performance_mode(properties.hint.PerformanceMode.LATENCY), - properties.hint.enable_cpu_pinning(True), - properties.hint.scheduling_core_type(properties.hint.SchedulingCoreType.PCORE_ONLY), - properties.hint.enable_hyper_threading(True), - properties.hint.num_requests(12), - properties.streams.num(5), + props.enable_profiling(True), + props.cache_dir("./"), + props.inference_num_threads(9), + props.affinity(props.Affinity.NONE), + hints.inference_precision(Type.f32), + hints.performance_mode(hints.PerformanceMode.LATENCY), + hints.enable_cpu_pinning(True), + hints.scheduling_core_type(hints.SchedulingCoreType.PCORE_ONLY), + hints.enable_hyper_threading(True), + hints.num_requests(12), + streams.num(5), ], ), # Pure dict { - properties.enable_profiling(): True, - properties.cache_dir(): "./", - properties.inference_num_threads(): 9, - properties.affinity(): properties.Affinity.NONE, - properties.hint.inference_precision(): Type.f32, - properties.hint.performance_mode(): properties.hint.PerformanceMode.LATENCY, - properties.hint.enable_cpu_pinning(): True, - properties.hint.scheduling_core_type(): properties.hint.SchedulingCoreType.PCORE_ONLY, - properties.hint.enable_hyper_threading(): True, - properties.hint.num_requests(): 12, - properties.streams.num(): 5, + props.enable_profiling(): True, + props.cache_dir(): "./", + props.inference_num_threads(): 9, + props.affinity(): props.Affinity.NONE, + hints.inference_precision(): Type.f32, + hints.performance_mode(): hints.PerformanceMode.LATENCY, + hints.enable_cpu_pinning(): True, + hints.scheduling_core_type(): hints.SchedulingCoreType.PCORE_ONLY, + hints.enable_hyper_threading(): True, + hints.num_requests(): 12, + streams.num(): 5, }, # Mixed dict { - properties.enable_profiling(): True, + props.enable_profiling(): True, "CACHE_DIR": "./", - properties.inference_num_threads(): 9, - properties.affinity(): "NONE", + props.inference_num_threads(): 9, + props.affinity(): "NONE", "INFERENCE_PRECISION_HINT": Type.f32, - properties.hint.performance_mode(): properties.hint.PerformanceMode.LATENCY, - properties.hint.scheduling_core_type(): properties.hint.SchedulingCoreType.PCORE_ONLY, - properties.hint.num_requests(): 12, - "NUM_STREAMS": properties.streams.Num(5), + hints.performance_mode(): hints.PerformanceMode.LATENCY, + hints.scheduling_core_type(): hints.SchedulingCoreType.PCORE_ONLY, + hints.num_requests(): 12, + "NUM_STREAMS": streams.Num(5), "ENABLE_MMAP": "NO", }, ], @@ -521,17 +530,17 @@ def test_core_cpu_properties(properties_to_set): core.set_property(properties_to_set) # RW properties - assert core.get_property("CPU", properties.enable_profiling()) is True - assert core.get_property("CPU", properties.cache_dir()) == "./" - assert core.get_property("CPU", properties.inference_num_threads()) == 9 - assert core.get_property("CPU", properties.affinity()) == properties.Affinity.NONE - assert core.get_property("CPU", properties.streams.num()) == 5 + assert core.get_property("CPU", props.enable_profiling()) is True + assert core.get_property("CPU", props.cache_dir()) == "./" + assert core.get_property("CPU", props.inference_num_threads()) == 9 + assert core.get_property("CPU", props.affinity()) == props.Affinity.NONE + assert core.get_property("CPU", streams.num()) == 5 # RO properties - assert type(core.get_property("CPU", properties.supported_properties())) == dict - assert type(core.get_property("CPU", properties.available_devices())) == list - assert type(core.get_property("CPU", properties.optimal_number_of_infer_requests())) == int - assert type(core.get_property("CPU", properties.range_for_streams())) == tuple - assert type(core.get_property("CPU", properties.range_for_async_infer_requests())) == tuple - assert type(core.get_property("CPU", properties.device.full_name())) == str - assert type(core.get_property("CPU", properties.device.capabilities())) == list + assert type(core.get_property("CPU", props.supported_properties())) == dict + assert type(core.get_property("CPU", props.available_devices())) == list + assert type(core.get_property("CPU", props.optimal_number_of_infer_requests())) == int + assert type(core.get_property("CPU", props.range_for_streams())) == tuple + assert type(core.get_property("CPU", props.range_for_async_infer_requests())) == tuple + assert type(core.get_property("CPU", device.full_name())) == str + assert type(core.get_property("CPU", device.capabilities())) == list From 2205f48c71ede01fdc59a909929c9dcf23065e6c Mon Sep 17 00:00:00 2001 From: Evgenya Nugmanova Date: Fri, 15 Sep 2023 12:27:12 +0400 Subject: [PATCH 06/12] Squeeze w/o axes [1, -1] -> dyn_rank (#19593) Removes PDPD logic from core code, keeps PDPD specifics in the translator --- .../include/squeeze_shape_inference.hpp | 32 +++++++++---------- src/core/tests/type_prop/squeeze.cpp | 8 ++++- src/frontends/paddle/src/op/slice_ops.hpp | 22 ++++++------- 3 files changed, 32 insertions(+), 30 deletions(-) diff --git a/src/core/shape_inference/include/squeeze_shape_inference.hpp b/src/core/shape_inference/include/squeeze_shape_inference.hpp index 774542b3edb477..d6c167975ac7d3 100644 --- a/src/core/shape_inference/include/squeeze_shape_inference.hpp +++ b/src/core/shape_inference/include/squeeze_shape_inference.hpp @@ -56,8 +56,7 @@ std::vector shape_infer(const Squeeze* op, OPENVINO_SUPPRESS_DEPRECATED_END unique_axes.reset(new std::set(axes->cbegin(), axes->cend())); } else if (arg_rank.get_length() > 0 && shape_size(axes_shape.to_shape()) == 1) { - // The `axes` input must be a Parameter with single element to ensure uniqueness of axes - // only rank is deduced + // The `axes` input is a single element tensor which is unique by definition, deducing output rank NODE_VALIDATION_CHECK(op, std::any_of(arg_shape.cbegin(), arg_shape.cend(), @@ -80,14 +79,21 @@ std::vector shape_infer(const Squeeze* op, if (arg_rank.is_static() && (unique_axes != nullptr)) { output_shape.resize(0); if (unique_axes->empty()) { - // According to specification, if only first input provided` or axes are empty - // remove all dimensions equal to 1. - std::copy_if(arg_shape.cbegin(), - arg_shape.cend(), - std::back_inserter(output_shape), - [](const DimType& dim) { - return !dim.compatible(1); - }); + // if only first input provided or axes are empty remove all dimensions equal to 1. + if (std::any_of(arg_shape.cbegin(), arg_shape.cend(), [](const DimType& d) { + return d.is_dynamic() && d.compatible(1); + })) { + // we are unsure if dynamic dimensions would be equal to 1 or not, so we set dynamic output rank + output_shape = PartialShape::dynamic(); + return output_shapes; + } else { + std::copy_if(arg_shape.cbegin(), + arg_shape.cend(), + std::back_inserter(output_shape), + [](const DimType& dim) { + return !dim.compatible(1); + }); + } } else { int64_t idx = 0; auto rm_axis_iter = unique_axes->cbegin(); @@ -111,12 +117,6 @@ std::vector shape_infer(const Squeeze* op, std::back_inserter(output_shape), not_squeezable_at_axis); } - // When arg shape has got static rank but shape is dynamic and output shape dimensions is empty (scalar) - // make dynamic output except the case when arg_shape is 1-D shape with 0 or 1 element then should be scalar. - if (arg_shape.is_dynamic() && (output_shape.size() == 0) && - !(arg_rank.get_length() == 1 && arg_shape[0].get_max_length() <= 1)) { - output_shape = PartialShape::dynamic(); - } } else { output_shape = PartialShape::dynamic(); } diff --git a/src/core/tests/type_prop/squeeze.cpp b/src/core/tests/type_prop/squeeze.cpp index 3047fb9acd03fa..7561a65c798d54 100644 --- a/src/core/tests/type_prop/squeeze.cpp +++ b/src/core/tests/type_prop/squeeze.cpp @@ -27,6 +27,12 @@ TEST(type_prop, squeeze_axes_invalid_value) { HasSubstr("provided axis value is invalid. Only axes of size 1 may be removed.")); } +TEST(type_prop, squeeze_single_input) { + auto param = make_shared(element::f32, PartialShape{1, -1, 3, 4}); + auto s = make_shared(param); + EXPECT_EQ(s->get_output_partial_shape(0), PartialShape::dynamic()); +} + TEST(type_prop, squeeze_axes_invalid_rank) { auto param = make_shared(element::f32, Shape{1, 2, 3, 4}); auto axes_node = make_shared(element::i32, Shape{2, 1}, vector{0, 2}); @@ -254,7 +260,7 @@ const auto empty_axes_test_values = std::vector{}, PartialShape{Dimension(2, 5), Dimension(3, 4), 6}), std::make_tuple(PartialShape::dynamic(6), std::vector{}, PartialShape::dynamic()), - std::make_tuple(PartialShape{Dimension(0, 1)}, std::vector{}, PartialShape{}), + std::make_tuple(PartialShape{Dimension(0, 1)}, std::vector{}, PartialShape::dynamic()), std::make_tuple(PartialShape{Dimension::dynamic(), 1, Dimension::dynamic()}, std::vector{}, PartialShape::dynamic()), diff --git a/src/frontends/paddle/src/op/slice_ops.hpp b/src/frontends/paddle/src/op/slice_ops.hpp index 37026111d15c91..dc2a609ba18513 100644 --- a/src/frontends/paddle/src/op/slice_ops.hpp +++ b/src/frontends/paddle/src/op/slice_ops.hpp @@ -91,26 +91,22 @@ NamedOutputs slice_op(const NodeContext& node, const bool& stride_input) { const auto decrease_axis = node.get_attribute>("decrease_axis"); if (decrease_axis.size() > 0) { - // according to paddle slice_op, when all axes are decreased, output shape is [1], instead of scalar. - // Ref: paddle/fluid/operators/slice_op.h PartialShape input_shape = data.get_partial_shape(); PADDLE_OP_CHECK(node, input_shape.rank().is_static(), "input rank of slice must be static when decrease_axis is set."); - + if (input_shape.size() == decrease_axis.size()) { + // according to paddle slice_op, when all axes are decreased, output shape is [1], instead of scalar. + // Ref: paddle/fluid/operators/slice_op.h + auto decreased_node = std::make_shared( + stride_slice_node, + std::make_shared(element::i64, Shape{1}, 1), + false); + return node.default_single_output_mapping({decreased_node}, {"Out"}); + } const auto squeeze_index_node = default_opset::Constant::create(element::i32, {decrease_axis.size()}, decrease_axis); const auto decreased_node = std::make_shared(stride_slice_node, squeeze_index_node); - - const auto input_rank = input_shape.rank().get_length(); - if ((size_t)input_rank == decrease_axis.size()) { - auto restore_node = std::make_shared( - decreased_node, - std::make_shared(element::i64, Shape{1}, 1), - false); // restore to shape (1,) - return node.default_single_output_mapping({restore_node}, {"Out"}); - } - return node.default_single_output_mapping({decreased_node}, {"Out"}); } From 5b6043069dad1e4430823a6cd6e7a6e02e51db1e Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Fri, 15 Sep 2023 08:49:24 +0000 Subject: [PATCH 07/12] Bump codecov/codecov-action from 3 to 4 (#19863) Bumps [codecov/codecov-action](https://github.com/codecov/codecov-action) from 3 to 4. - [Release notes](https://github.com/codecov/codecov-action/releases) - [Changelog](https://github.com/codecov/codecov-action/blob/main/CHANGELOG.md) - [Commits](https://github.com/codecov/codecov-action/compare/v3...v4) --- updated-dependencies: - dependency-name: codecov/codecov-action dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> --- .github/workflows/coverage.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml index 29cf3cd8afc34f..8e375e63cbacc5 100644 --- a/.github/workflows/coverage.yml +++ b/.github/workflows/coverage.yml @@ -144,6 +144,6 @@ jobs: lcov --capture --directory ${{ github.workspace }}/. --output-file coverage.info genhtml coverage.info --output-directory coverage-report - name: Collect coverage - uses: codecov/codecov-action@v3 + uses: codecov/codecov-action@v4 with: verbose: true From 2ec80439d715dbd18af708bdc9a128020df9b3b2 Mon Sep 17 00:00:00 2001 From: Karol Blaszczak Date: Fri, 15 Sep 2023 11:50:21 +0200 Subject: [PATCH 08/12] [DOCS] benchmark update 23.1 (#19683) --- .../OV-2023.0-Performance-Data.xlsx | Bin 326534 -> 167725 bytes .../OV-2023.0-system-info-detailed.xlsx | Bin 72517 -> 0 bytes ...m_list.pdf => OV-2023.1-Platform_list.pdf} | Bin 215404 -> 205520 bytes .../OV-2023.1-system-info-detailed.xlsx | Bin 0 -> 67988 bytes .../benchmarks_files/OV-benchmark-data.csv | 44 ++-- docs/benchmarks/performance_benchmarks.md | 6 +- docs/benchmarks/performance_benchmarks_faq.md | 43 ++-- docs/benchmarks/performance_int8_vs_fp32.md | 235 +++++++++--------- 8 files changed, 162 insertions(+), 166 deletions(-) delete mode 100644 docs/_static/benchmarks_files/OV-2023.0-system-info-detailed.xlsx rename docs/_static/benchmarks_files/{OV-2023.0-Platform_list.pdf => OV-2023.1-Platform_list.pdf} (70%) create mode 100644 docs/_static/benchmarks_files/OV-2023.1-system-info-detailed.xlsx diff --git a/docs/_static/benchmarks_files/OV-2023.0-Performance-Data.xlsx b/docs/_static/benchmarks_files/OV-2023.0-Performance-Data.xlsx index 18ced16236b750f599bc8c2682c27f0d98464d09..f4000d00ce058e92e2d896248bba3adb75bc7678 100644 GIT binary patch delta 120367 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z|6Rp@ZG^zr2I`q%AfOv?Fd&To(DMoV|1{!%Fs6Udr9c15pP2>!D1uo0uXzT4D)^Hd z`HzC&jejZlhbj4|=$~wde?%`2{ucd{`|ziRKasV6H1q>5?EhSd|2LfNPlbQN0{AEgKY=MHG)e}pi9O8;k=@Q*AI&>BGce+3PHivQ;@|L@`& eApa)*KZCxUBpASg|6;kq0U7>fpx}Q+AO8nRz}R8{ literal 0 HcmV?d00001 diff --git a/docs/_static/benchmarks_files/OV-benchmark-data.csv b/docs/_static/benchmarks_files/OV-benchmark-data.csv index 8fbc20e6e64f3b..ea2a4cd4de414f 100644 --- a/docs/_static/benchmarks_files/OV-benchmark-data.csv +++ b/docs/_static/benchmarks_files/OV-benchmark-data.csv @@ -5,7 +5,7 @@ bert-base-cased,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,21.38,,15.11,0. bert-base-cased,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,32.23,,20.26,0.15061144,0.495859202,214,65,1,214,65,36.18,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,113.18,,45.08,0.344024364,0.905472125,329,125,1,329,125,17.43,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,34.34,,24.04,0.178867029,0.528345686,192,65,1,192,65,30.88,FPS,FPS/$,FPS/TDP,msec. -bert-base-cased,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +bert-base-cased,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,51.27,,18.44,0.120345681,1.830973571,426,28,1,426,28,23.31,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,37.98,,13.59,0.077518083,1.356566444,490,28,1,490,28,29.22,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,27.60,,17.56,0.091086845,0.788551831,303,35,1,303,35,42.83,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,34.12,,20.30,0.069915909,0.974827538,488,35,1,488,35,37.09,FPS,FPS/$,FPS/TDP,msec. @@ -29,7 +29,7 @@ bert-base-cased,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,84.42, bert-base-cased,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,46.67,,23.26,0.436174206,3.111376,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,73.20,,31.70,0.149385536,2.614246884,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. bert-base-cased,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,4.43,,2.03,0.022934748,0.7377344,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -bert-base-cased,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +bert-base-cased,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,83.69,,37.23,0.196445915,2.988784286,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,1.18,,0.38,0.011017319,0.078590206,107,15,1,107,15,863.34,FPS,FPS/$,FPS/TDP,msec. @@ -37,7 +37,7 @@ bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,2.97,,1.87,0.013882493,0.045705439,214,65,1,214,65,347.78,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,9.93,,3.74,0.030176091,0.079423471,329,125,1,329,125,155.72,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,3.36,,2.13,0.017518449,0.051746803,192,65,1,192,65,302.24,FPS,FPS/$,FPS/TDP,msec. -bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,5.09,,1.63,0.011951214,0.181829179,426,28,1,426,28,219.77,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,3.79,,1.22,0.007726669,0.135216715,490,28,1,490,28,266.14,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,2.71,,1.61,0.008936965,0.077368581,303,35,1,303,35,412.44,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,3.35,,1.83,0.006861724,0.095672042,488,35,1,488,35,327.59,FPS,FPS/$,FPS/TDP,msec. @@ -61,7 +61,7 @@ bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-iGPU,Intel® Co bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,5.20,,2.33,0.048610495,0.346754867,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,3.87,,2.23,0.007899318,0.138238071,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,0.44,,0.17,0.002288653,0.073618327,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +bert-large-uncased-whole-word-masking-squad-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,8.63,,3.52,0.02025661,0.308189857,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,11.86,,4.61,0.11084032,0.79066095,107,15,1,107,15,85.88,FPS,FPS/$,FPS/TDP,msec. @@ -69,7 +69,7 @@ deeplabv3,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,22.85,,14.48,0.195256 deeplabv3,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,34.47,,16.42,0.161068212,0.530286114,214,65,1,214,65,33.07,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,94.13,,42.32,0.286105004,0.753028371,329,125,1,329,125,16.23,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,37.18,,21.16,0.193650962,0.572015148,192,65,1,192,65,27.36,FPS,FPS/$,FPS/TDP,msec. -deeplabv3,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +deeplabv3,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,52.88,,16.51,0.124135164,1.888627857,426,28,1,426,28,19.87,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,30.78,,9.65,0.062807791,1.099136335,490,28,1,490,28,31.13,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,32.02,,18.34,0.105688204,0.914957883,303,35,1,303,35,37.47,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,40.36,,18.54,0.082712269,1.153245355,488,35,1,488,35,27.15,FPS,FPS/$,FPS/TDP,msec. @@ -93,7 +93,7 @@ deeplabv3,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,105.14,48.76 deeplabv3,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,61.90,,17.22,0.578511308,4.126714,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,49.44,,9.02,0.100894422,1.765652381,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. deeplabv3,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,4.81,,2.03,0.024920889,0.801621937,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -deeplabv3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +deeplabv3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,89.16,,24.78,0.209304953,3.184425357,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,272.36,,133.20,2.545454771,18.15757736,107,15,1,107,15,3.60,FPS,FPS/$,FPS/TDP,msec. @@ -101,7 +101,7 @@ mobilenet-v2,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,542.97,,451.26,4.6 mobilenet-v2,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,899.54,,499.68,4.203451742,13.8390565,214,65,1,214,65,1.58,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,2804.17,,1285.76,8.523326054,22.43339417,329,125,1,329,125,0.88,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,868.27,,679.32,4.522249945,13.35803061,192,65,1,192,65,1.35,FPS,FPS/$,FPS/TDP,msec. -mobilenet-v2,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +mobilenet-v2,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,1372.54,,531.48,3.221931925,49.01939286,426,28,1,426,28,0.96,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,990.18,,318.31,2.020773404,35.36353457,490,28,1,490,28,1.18,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,741.91,,511.96,2.448553162,21.19747452,303,35,1,303,35,1.84,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,960.08,,614.86,1.967381666,27.43092151,488,35,1,488,35,1.49,FPS,FPS/$,FPS/TDP,msec. @@ -125,7 +125,7 @@ mobilenet-v2,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,1008.77,7 mobilenet-v2,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,514.94,,313.82,4.812519626,34.32930667,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,1114.75,,268.28,2.275002757,39.81254825,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. mobilenet-v2,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,73.89,,44.62,0.38286464,12.31547925,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -mobilenet-v2,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +mobilenet-v2,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,1497.43,,605.84,3.515084507,53.4795,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,49.96,,14.45,0.466891776,3.330494671,107,15,1,107,15,19.80,FPS,FPS/$,FPS/TDP,msec. @@ -133,7 +133,7 @@ resnet-50,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,97.49,,51.23,0.833227 resnet-50,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,145.23,,74.40,0.678644387,2.234306135,214,65,1,214,65,8.18,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,515.94,,140.29,1.568210731,4.127530643,329,125,1,329,125,3.87,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,158.18,,82.33,0.823856129,2.433544259,192,65,1,192,65,7.04,FPS,FPS/$,FPS/TDP,msec. -resnet-50,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +resnet-50,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,229.98,,61.97,0.539855399,8.213514286,426,28,1,426,28,5.09,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,173.03,,44.88,0.353117963,6.179564359,490,28,1,490,28,6.59,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,122.85,,61.90,0.405448145,3.510022512,303,35,1,303,35,9.95,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,158.96,,76.32,0.325734087,4.541663835,488,35,1,488,35,7.54,FPS,FPS/$,FPS/TDP,msec. @@ -157,7 +157,7 @@ resnet-50,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,352.09,211.3 resnet-50,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,201.96,,71.44,1.887469159,13.46394667,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,307.08,,88.49,0.626686058,10.96700601,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. resnet-50,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,18.58,,6.49,0.09624999,3.096041335,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -resnet-50,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +resnet-50,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,358.14,,114.23,0.840715023,12.79087857,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,107.63,,36.80,1.005906996,7.175469906,107,15,1,107,15,9.12,FPS,FPS/$,FPS/TDP,msec. @@ -165,7 +165,7 @@ ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,212.15,,1 ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,327.95,,171.39,1.532485774,5.045414702,214,65,1,214,65,3.61,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,999.78,,361.81,3.038835794,7.99821581,329,125,1,329,125,1.90,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,343.23,,200.57,1.787633018,5.280392915,192,65,1,192,65,3.11,FPS,FPS/$,FPS/TDP,msec. -ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,518.48,,150.36,1.217089202,18.51714286,426,28,1,426,28,2.24,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,387.68,,101.48,0.791191606,13.8458531,490,28,1,490,28,2.80,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,275.38,,157.24,0.908858835,7.868120772,303,35,1,303,35,4.33,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,367.82,,194.43,0.753734827,10.50921702,488,35,1,488,35,3.35,FPS,FPS/$,FPS/TDP,msec. @@ -189,7 +189,7 @@ ssd_mobilenet_v1_coco,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only, ssd_mobilenet_v1_coco,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,321.29,,138.22,3.002740187,21.41954667,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,531.28,,141.48,1.084245141,18.97428996,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. ssd_mobilenet_v1_coco,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,35.69,,14.88,0.184945841,5.949091211,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -ssd_mobilenet_v1_coco,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +ssd_mobilenet_v1_coco,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,690.18,,239.85,1.620143192,24.64932143,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,0.89,,0.23,0.00834996,0.059563049,107,15,1,107,15,1119.27,FPS,FPS/$,FPS/TDP,msec. @@ -197,7 +197,7 @@ ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,1.68,,0.97,0. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,2.42,,1.40,0.011301245,0.037207176,214,65,1,214,65,459.48,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,8.23,,2.40,0.025006186,0.065816281,329,125,1,329,125,163.47,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,2.78,,1.56,0.014501179,0.042834252,192,65,1,192,65,362.12,FPS,FPS/$,FPS/TDP,msec. -ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,3.93,,1.00,0.009217819,0.140242536,426,28,1,426,28,278.25,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,2.96,,0.76,0.006043555,0.105762215,490,28,1,490,28,336.81,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,2.02,,1.13,0.006664408,0.057694728,303,35,1,303,35,563.91,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,2.68,,1.49,0.00548551,0.076483685,488,35,1,488,35,405.46,FPS,FPS/$,FPS/TDP,msec. @@ -221,7 +221,7 @@ ssd-resnet34-1200,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,9.70 ssd-resnet34-1200,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,0.90,,0.23,0.00837685,0.059754867,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,2.91,,0.75,0.005937663,0.103909111,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. ssd-resnet34-1200,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,0.11,,0.05,0.000582108,0.01872448,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -ssd-resnet34-1200,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +ssd-resnet34-1200,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,3.92,,1.00,0.00919669,0.139921071,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,5.46,,1.54,0.051044248,0.364115633,107,15,1,107,15,183.90,FPS,FPS/$,FPS/TDP,msec. @@ -229,7 +229,7 @@ yolo-v3,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,10.65,,5.82,0.09106238, yolo-v3,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,15.38,,8.31,0.071851432,0.236557023,214,65,1,214,65,74.19,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,51.71,,15.62,0.157162207,0.41365093,329,125,1,329,125,29.85,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,17.56,,9.38,0.091438134,0.270094181,192,65,1,192,65,57.84,FPS,FPS/$,FPS/TDP,msec. -yolo-v3,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo-v3,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,24.16,,6.62,0.056714953,0.8628775,426,28,1,426,28,45.99,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,18.06,,4.86,0.03686323,0.645106519,490,28,1,490,28,57.19,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,12.66,,6.85,0.041784766,0.361736687,303,35,1,303,35,86.80,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,16.86,,8.71,0.034540452,0.48159259,488,35,1,488,35,65.99,FPS,FPS/$,FPS/TDP,msec. @@ -253,7 +253,7 @@ yolo-v3,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,63.86,29.69,,0 yolo-v3,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,34.09,,9.18,0.318603364,2.272704,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,55.18,,12.97,0.112605748,1.970600588,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. yolo-v3,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,2.22,,0.74,0.011488536,0.369547916,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -yolo-v3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo-v3,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,52.21,,13.99,0.122567488,1.864776786,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,54.42,,18.04,0.508553978,3.627685044,107,15,1,107,15,18.25,FPS,FPS/$,FPS/TDP,msec. @@ -261,7 +261,7 @@ yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,112.01,,63.79,0.95 yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,167.15,,91.46,0.781091755,2.571594392,214,65,1,214,65,6.72,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,599.98,,196.78,1.823638134,4.799815567,329,125,1,329,125,3.05,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,185.17,,102.47,0.964441757,2.848812574,192,65,1,192,65,5.42,FPS,FPS/$,FPS/TDP,msec. -yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,251.02,,77.47,0.589250939,8.965032143,426,28,1,426,28,4.54,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,186.99,,55.22,0.381609578,6.678167613,490,28,1,490,28,5.74,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,137.72,,76.53,0.454530194,3.934932821,303,35,1,303,35,8.20,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,186.09,,96.75,0.381340728,5.316979292,488,35,1,488,35,6.26,FPS,FPS/$,FPS/TDP,msec. @@ -285,7 +285,7 @@ yolo-v3-tiny,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,555.59,29 yolo-v3-tiny,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,266.57,,93.47,2.491299065,17.77126667,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,383.36,,116.03,0.782374111,13.69154694,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. yolo-v3-tiny,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,23.03,,8.30,0.119308014,3.837741122,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -yolo-v3-tiny,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo-v3-tiny,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,444.34,,149.05,1.043043427,15.86916071,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,1.49,,0.38,0.013950494,0.099513526,107,15,1,107,15,672.25,FPS,FPS/$,FPS/TDP,msec. @@ -293,7 +293,7 @@ unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,2.43,,1.5 unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,3.62,,2.29,0.016924989,0.055722272,214,65,1,214,65,322.49,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,11.46,,3.96,0.03483307,0.091680639,329,125,1,329,125,121.88,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,3.95,,2.54,0.020576722,0.06078047,192,65,1,192,65,262.38,FPS,FPS/$,FPS/TDP,msec. -unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,6.56,,1.65,0.015387439,0.234108893,426,28,1,426,28,169.32,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,4.93,,1.23,0.010063508,0.176111389,490,28,1,490,28,209.95,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,3.02,,1.85,0.009976084,0.086364383,303,35,1,303,35,386.94,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,3.86,,2.43,0.007900388,0.110153975,488,35,1,488,35,282.08,FPS,FPS/$,FPS/TDP,msec. @@ -317,7 +317,7 @@ unet-camvid-onnx-0001,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only, unet-camvid-onnx-0001,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,8.96,,2.57,0.083779393,0.597626333,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,15.42,,3.90,0.031467977,0.550689601,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. unet-camvid-onnx-0001,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,0.55,,0.19,0.002833692,0.09115042,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -unet-camvid-onnx-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +unet-camvid-onnx-0001,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,14.32,,3.81,0.033621549,0.511527857,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,24.40,,9.61,0.22800938,1.626466914,107,15,1,107,15,40.45,FPS,FPS/$,FPS/TDP,msec. @@ -325,7 +325,7 @@ yolo_v8n,OV-2023.1,core,Intel® Core™ i3-8100 CPU-only,53.51,,33.07,0.4573632 yolo_v8n,OV-2023.1,core,Intel® Core™ i5-10500TE CPU-only,81.91,,47.09,0.382748211,1.260124878,214,65,1,214,65,13.68,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core,Intel® Core™ i5-13600K CPU-only,248.13,,95.51,0.754209583,1.985079623,329,125,1,329,125,6.70,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core,Intel® Core™ i5-8500 CPU-only,86.77,,53.00,0.451947196,1.334982486,192,65,1,192,65,11.88,FPS,FPS/$,FPS/TDP,msec. -yolo_v8n,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo_v8n,OV-2023.1,core,Intel® Core™ i7-1185G7 CPU-only,110.84,,40.77,0.260193662,3.958660714,426,28,1,426,28,10.71,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core,Intel® Core™ i7-1185GRE CPU-only,76.53,,27.31,0.156180065,2.733151145,490,28,1,490,28,13.42,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core,Intel® Core™ i7-8700T CPU-only,71.40,,42.60,0.235643867,2.040002619,303,35,1,303,35,16.51,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core,Intel® Core™ i9-10900TE CPU-only,93.44,,53.42,0.19148001,2.669778431,488,35,1,488,35,12.45,FPS,FPS/$,FPS/TDP,msec. @@ -349,7 +349,7 @@ yolo_v8n,OV-2023.1,core-iGPU,Intel® Core™ i7-1185G7 iGPU-only,210.16,143.23 yolo_v8n,OV-2023.1,core-CPU+iGPU,Intel® Celeron™ 6305E CPU+iGPU,116.50,,51.35,1.088790654,7.766706667,107,15,1,107,15,,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185GRE CPU+iGPU,114.23,,46.77,0.233123263,4.079657102,490,28,1,490,28,,FPS,FPS/$,FPS/TDP,msec. yolo_v8n,OV-2023.1,core-CPU+iGPU,Intel® Processor N200 CPU+iGPU,10.54,,4.68,0.05458634,1.755860615,193,6,1,193,6,,FPS,FPS/$,FPS/TDP,msec. -yolo_v8n,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,,,,0,0,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. +yolo_v8n,OV-2023.1,core-CPU+iGPU,Intel® Core™ i7-1185G7 CPU+iGPU,181.83,,76.10,0.426834977,6.493989286,426,28,1,426,28,,FPS,FPS/$,FPS/TDP,msec. end_rec,,,,,,,,,,,,,,,,,, begin_rec,,,,,,,,,,,,,,,msec/token,msec/token/$,msec/token/TDP,msec. bloomz-560m,OV-2023.1,atom,Intel® Celeron™ 6305E CPU-only,,,,0,0,107,15,1,107,15,,msec/token,msec/token/$,msec/token/TDP,msec. diff --git a/docs/benchmarks/performance_benchmarks.md b/docs/benchmarks/performance_benchmarks.md index 9c95329e184726..a322a2a66af593 100644 --- a/docs/benchmarks/performance_benchmarks.md +++ b/docs/benchmarks/performance_benchmarks.md @@ -100,14 +100,14 @@ For a listing of all platforms and configurations used for testing, refer to the .. grid-item:: - .. button-link:: _static/benchmarks_files/OV-2023.0-Platform_list.pdf + .. button-link:: _static/benchmarks_files/OV-2023.1-Platform_list.pdf :color: primary :outline: :expand: :material-regular:`download;1.5em` Click for Hardware Platforms [PDF] - .. button-link:: _static/benchmarks_files/OV-2023.0-system-info-detailed.xlsx + .. button-link:: _static/benchmarks_files/OV-2023.1-system-info-detailed.xlsx :color: primary :outline: :expand: @@ -166,7 +166,7 @@ or `create an account `__ - - OpenAI GPT-2 + * - `BLOOMZ-560M `__ + - BigScience Bloomz & MT0 + - Transformer based llm + - 2048 + * - `GPT-J-6B `__ + - Eleuther AI - Transformer - - 1024 + - 2048 + * - `Llama-2-7b-chat `__ + - Meta AI + - Auto regressive language + - 4096 + * - `Stable-Diffusion-V2-1 `__ + - Hugginface + - Latent Diffusion Model + - 77 * - `bert-base-cased `__ - BERT - question / answer @@ -62,22 +77,6 @@ - DeepLab v3 Tf - semantic segmentation - 513x513 - * - `efficientdet-d0 `__ - - Efficientdet - - classification - - 512x512 - * - `faster_rcnn_resnet50_coco `__ - - Faster RCNN Tf - - object detection - - 600x1024 - * - `inception-v4 `__ - - Inception v4 (aka GoogleNet-V4) - - classification - - 299x299 - * - `mobilenet-ssd `__ - - SSD (MobileNet)_COCO-2017_Caffe - - object detection - - 300x300 * - `mobilenet-v2 `__ - Mobilenet V2 PyTorch - classification @@ -86,6 +85,10 @@ - ResNet-50_v1_ILSVRC-2012 - classification - 224x224 + * - `ssd-mobilenet-v1-coco `__ + - ssd-mobilenet-V1-coco onnx model + - object detection + - 300x300 * - `ssd-resnet34-1200-onnx `__ - ssd-resnet34 onnx model - object detection diff --git a/docs/benchmarks/performance_int8_vs_fp32.md b/docs/benchmarks/performance_int8_vs_fp32.md index b28cb4e0d9796d..6652be32dc21fa 100644 --- a/docs/benchmarks/performance_int8_vs_fp32.md +++ b/docs/benchmarks/performance_int8_vs_fp32.md @@ -1,17 +1,12 @@ -# OpenVINO Accuracy {#openvino_docs_performance_int8_vs_fp32} +# Model Accuracy {#openvino_docs_performance_int8_vs_fp32} @sphinxdirective -.. meta:: - :description: Learn about the differences in absolute accuracy drop for INT8, - FP32 and FP16 representations of models inferred with OpenVINO - on three different platforms. - The following two tables present the absolute accuracy drop calculated as the accuracy difference between OV-accuracy and the original frame work accuracy for FP32, and the same for INT8 and FP16 representations of a model on three platform architectures. Please also refer to notes below table -for more information. +for more information. * A - Intel® Core™ i9-9000K (AVX2), INT8 and FP32 * B - Intel® Xeon® 6338, (VNNI), INT8 and FP32 @@ -27,98 +22,98 @@ for more information. - A, INT8 - B, INT8 - C, INT8 - * - GPT-2 - - WikiText_2_raw_gpt2 - - perplexity - - n/a - - n/a - - n/a * - bert-base-cased - SST-2_bert_cased_padded - accuracy - - 1.15% - - 1.51% - - -0.85% + - -3.00% + - -2.00% + - 2.94% * - bert-large-uncased-whole-word-masking-squad-0001 - SQUAD_v1_1_bert_msl384_mql64_ds128_lowercase - F1 - - 0.05% - - 0.11% - - 0.10% + - -0.04% + - 0.03% + - 0.06% * - deeplabv3 - VOC2012_segm - mean_iou - - -0.46% - - -0.23% - - -0.18% - * - efficientdet-d0 - - COCO2017_detection_91cl - - coco_precision - - -0.87% - - -0.56% - - n/a - * - faster_rcnn_resnet50_coco - - COCO2017_detection_91cl_bkgr - - coco_precision - - -0.24% - - -0.24% - - 0.00% - * - inception-v4 - - ImageNet2012_bkgr - - accuracy @ top1 - - -0.06% - - -0.08% - - -0.04% - * - mobilenet-ssd - - VOC2007_detection - - map - - -0.49% - - -0.50% - - -0.47% + - 0.00% + - 0.23% + - -0.13% * - mobilenet-v2 - ImageNet2012 - accuracy @ top1 - - -0.70% - - -1.11% - - -1.05% + - + - 0.97% + - -0.97% * - resnet-50 - ImageNet2012 - accuracy @ top1 - - -0.13% - - -0.11% - - -0.14% + - 0.20% + - 0.12% + - -0.19% + * - ssd-mobilenet-v1-coco + - COCO2017_detection_80cl_bkgr + - coco-precision + - 2.97% + - 0.29% + - -0.31% * - ssd-resnet34-1200 - COCO2017_detection_80cl_bkgr - map - - -0.02% - - -0.03% - - 0.04% + - 0.06% + - 0.06% + - -0.06% * - unet-camvid-onnx-0001 - CamVid_12cl - mean_iou @ mean - - n/a - - 6.40% - - -0.30% + - 6.32% + - -6.40% + - -0.63% * - yolo_v3 - COCO2017_detection_80cl - map - - -0.14% - - -0.01% - - -0.19% + - -0.06% + - -0.21% + - -0.71% * - yolo_v3_tiny - COCO2017_detection_80cl - map - - -0.11% - - -0.13% - - -0.17% + - 0.73% + - 0.21% + - -0.78% * - yolo_v8n - COCO2017_detection_80cl - map - - n/a - - n/a - - n/a + - -0.26% + - -0.22% + - 0.12% + * - bloomz-560m + - ROOTS corpus + - ppl + - + - + - + * - GPT-J-6B + - Pile dataset + - ppl + - + - 4.11 + - 4.11 + * - Llama-2-7b-chat + - Wiki, StackExch, Crawl + - ppl + - + - 3.27 + - 3.27 + * - Stable-Diffusion-V2-1 + - LIAON-5B + - ppl + - + - + - -.. list-table:: Model Accuracy for FP32 and FP16 (Flex-170 only) +.. list-table:: Model Accuracy for FP32 and FP16 (FP16: Flex-170 only) :header-rows: 1 * - OpenVINO™ Model name @@ -127,100 +122,98 @@ for more information. - A, FP32 - B, FP32 - C, FP16 - * - GPT-2 - - WikiText_2_raw_gpt2 - - perplexity - - -9.12% - - -9.12% - - -9.12% * - bert-base-cased - SST-2_bert_cased_padded - accuracy - 0.00% - 0.00% - - 0.01% + - 0.00% * - bert-large-uncased-whole-word-masking-squad-0001 - SQUAD_v1_1_bert_msl384_mql64_ds128_lowercase - F1 + - -0.19% - 0.04% - 0.04% - - 0.05% * - deeplabv3 - VOC2012_segm - mean_iou + - 0.49% - 0.00% - 0.00% - - 0.01% - * - efficientdet-d0 - - COCO2017_detection_91cl - - coco_precision - - -0.01% - - 0.02% - - 0.02% - * - faster_rcnn_resnet50_coco - - COCO2017_detection_91cl_bkgr - - coco_precision - - 0.00% - - -0.01% - - 0.03% - * - inception-v4 - - ImageNet2012_bkgr + * - mobilenet-v2 + - ImageNet2012 - accuracy @ top1 - 0.00% - 0.00% - - 0.01% - * - mobilenet-ssd - - VOC2007_detection - - map - - 0.00% - 0.00% - - 0.02% - * - mobilenet-v2 - - ImageNet2012 - - accuracy @ top1 - - -0.08% - - -0.08% - - 0.06% * - resnet-50 - ImageNet2012 - accuracy @ top1 - 0.00% + - -0.02% - 0.00% - - 0.00% + * - ssd-mobilenet-v1-coco + - COCO2017_detection_80cl_bkgr + - coco-precision + - 0.01% + - 0.01% + - 0.01% * - ssd-resnet34-1200 - COCO2017_detection_80cl_bkgr - map - - 0.00% - - 0.00% - - 0.02% + - 0.01% + - 0.06% + - -0.06% * - unet-camvid-onnx-0001 - CamVid_12cl - mean_iou @ mean - - -0.02% - - -0.02% - - 0.05% + - 0.02% + - -6.45% + - 6.45% * - yolo_v3 - COCO2017_detection_80cl - map - - 0.02% - - 0.02% - - 0.03% + - 0.00% + - 0.01% + - 0.01% * - yolo_v3_tiny - COCO2017_detection_80cl - map - - -0.04% - - -0.04% - - 0.03% + - 0.00% + - -0.02% + - 0.02% * - yolo_v8n - COCO2017_detection_80cl - map - 0.00% - 0.00% - - 0.03% + - 0.00% + * - bloomz-560m + - ROOTS corpus + - ppl + - + - 22.89 + - 22.89 + * - GPT-J-6B + - Pile dataset + - ppl + - + - 4.10 + - 4.10 + * - Llama-2-7b-chat + - Wiki, StackExch, Crawl + - ppl + - + - 2.91 + - 2.91 + * - Stable-Diffusion-V2-1 + - LIAON-5B + - ppl + - + - + - -.. note:: - - For all accuracy metrics except perplexity a "-" (minus sign) indicates an accuracy drop. - For perplexity a "-" indicates improved accuracy. +Notes: For all accuracy metrics except perplexity a "-", (minus sign), indicates an accuracy drop. +For perplexity the values do not indicate a deviation from a reference but are the actual measured accuracy for the model. @endsphinxdirective \ No newline at end of file From 68ba8873a2f87939616cb4ae99c65d28f22a4e29 Mon Sep 17 00:00:00 2001 From: Anastasia Kuporosova Date: Fri, 15 Sep 2023 14:19:44 +0200 Subject: [PATCH 09/12] [Docs] Update python snippets with new properties imports (#19872) --- docs/snippets/cpu/Bfloat16Inference.py | 10 +++-- docs/snippets/cpu/ov_execution_mode.py | 7 ++-- .../cpu/ov_sparse_weights_decompression.py | 4 +- docs/snippets/gpu/compile_model.py | 4 +- docs/snippets/ov_auto.py | 42 +++++++++++-------- docs/snippets/ov_auto_batching.py | 4 +- docs/snippets/ov_caching.py | 6 ++- docs/snippets/ov_denormals.py | 4 +- docs/snippets/ov_hetero.py | 13 ++++-- docs/snippets/ov_multi.py | 20 +++++---- docs/snippets/ov_properties_api.py | 13 +++--- docs/snippets/ov_properties_migration.py | 14 ++++--- 12 files changed, 86 insertions(+), 55 deletions(-) diff --git a/docs/snippets/cpu/Bfloat16Inference.py b/docs/snippets/cpu/Bfloat16Inference.py index 2d3fabfe6c4c29..7d6516ea7d46fb 100644 --- a/docs/snippets/cpu/Bfloat16Inference.py +++ b/docs/snippets/cpu/Bfloat16Inference.py @@ -1,8 +1,10 @@ -# Copyright (C) 2022 Intel Corporation +# Copyright (C) 2018-2023 Intel Corporation # SPDX-License-Identifier: Apache-2.0 import openvino as ov +import openvino.properties.device as device +import openvino.properties.hint as hints from snippets import get_model @@ -10,16 +12,16 @@ #! [part0] core = ov.Core() -cpu_optimization_capabilities = core.get_property("CPU", ov.properties.device.capabilities()) +cpu_optimization_capabilities = core.get_property("CPU", device.capabilities()) #! [part0] #! [part1] core = ov.Core() compiled_model = core.compile_model(model, "CPU") -inference_precision = core.get_property("CPU", ov.properties.hint.inference_precision()) +inference_precision = core.get_property("CPU", hints.inference_precision()) #! [part1] #! [part2] core = ov.Core() -core.set_property("CPU", {ov.properties.hint.inference_precision(): ov.Type.f32}) +core.set_property("CPU", {hints.inference_precision(): ov.Type.f32}) #! [part2] diff --git a/docs/snippets/cpu/ov_execution_mode.py b/docs/snippets/cpu/ov_execution_mode.py index 2feff2777f7d27..5476426e77aa7f 100644 --- a/docs/snippets/cpu/ov_execution_mode.py +++ b/docs/snippets/cpu/ov_execution_mode.py @@ -1,18 +1,19 @@ -# Copyright (C) 2023 Intel Corporation +# Copyright (C) 2018-2023 Intel Corporation # SPDX-License-Identifier: Apache-2.0 #! [ov:execution_mode:part0] import openvino as ov +import openvino.properties.hint as hints core = ov.Core() # in case of Accuracy core.set_property( "CPU", - {ov.properties.hint.execution_mode(): ov.properties.hint.ExecutionMode.ACCURACY}, + {hints.execution_mode(): hints.ExecutionMode.ACCURACY}, ) # in case of Performance core.set_property( "CPU", - {ov.properties.hint.execution_mode(): ov.properties.hint.ExecutionMode.PERFORMANCE}, + {hints.execution_mode(): hints.ExecutionMode.PERFORMANCE}, ) #! [ov:execution_mode:part0] diff --git a/docs/snippets/cpu/ov_sparse_weights_decompression.py b/docs/snippets/cpu/ov_sparse_weights_decompression.py index 76de90311d28ad..9a2a0f1480832f 100644 --- a/docs/snippets/cpu/ov_sparse_weights_decompression.py +++ b/docs/snippets/cpu/ov_sparse_weights_decompression.py @@ -10,8 +10,10 @@ device_name = "CPU" xml_path = "model.xml" # ! [ov:intel_cpu:sparse_weights_decompression:part0] +import openvino.properties.intel_cpu as intel_cpu + core = ov.Core() -core.set_property("CPU", ov.properties.intel_cpu.sparse_weights_decompression_rate(0.8)) +core.set_property("CPU", intel_cpu.sparse_weights_decompression_rate(0.8)) compiled_model = core.compile_model(model=model, device_name=device_name) # ! [ov:intel_cpu:sparse_weights_decompression:part0] assert compiled_model diff --git a/docs/snippets/gpu/compile_model.py b/docs/snippets/gpu/compile_model.py index 15e67d41ab0ca7..152de661c1f7ab 100644 --- a/docs/snippets/gpu/compile_model.py +++ b/docs/snippets/gpu/compile_model.py @@ -39,12 +39,14 @@ def main(): #! [compile_model_batch_plugin] #! [compile_model_auto_batch] + import openvino.properties.hint as hints + core = ov.Core() compiled_model = core.compile_model( model, "GPU", { - ov.properties.hint.performance_mode(): ov.properties.hint.PerformanceMode.THROUGHPUT, + hints.performance_mode(): hints.PerformanceMode.THROUGHPUT, }, ) #! [compile_model_auto_batch] diff --git a/docs/snippets/ov_auto.py b/docs/snippets/ov_auto.py index e0dc58587a4df9..35454e0527b6f1 100644 --- a/docs/snippets/ov_auto.py +++ b/docs/snippets/ov_auto.py @@ -1,5 +1,13 @@ -import sys +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 +# + import openvino as ov +import openvino.properties as properties +import openvino.properties.device as device +import openvino.properties.hint as hints +import openvino.properties.log as log + from openvino.inference_engine import IECore from utils import get_model, get_ngraph_model @@ -23,13 +31,13 @@ def part0(): compiled_model = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.device.priorities(): "GPU,CPU"}, + config={device.priorities(): "GPU,CPU"}, ) # Optional # the AUTO plugin is pre-configured (globally) with the explicit option: core.set_property( - device_name="AUTO", properties={ov.properties.device.priorities(): "GPU,CPU"} + device_name="AUTO", properties={device.priorities(): "GPU,CPU"} ) #! [part0] @@ -52,13 +60,13 @@ def part1(): exec_net = ie.load_network( network=net, device_name="AUTO", - config={ov.properties.device.priorities(): "GPU,CPU"}, + config={device.priorities(): "GPU,CPU"}, ) # Optional # the AUTO plugin is pre-configured (globally) with the explicit option: ie.set_config( - config={ov.properties.device.priorities(): "GPU,CPU"}, device_name="AUTO" + config={device.priorities(): "GPU,CPU"}, device_name="AUTO" ) #! [part1] @@ -73,7 +81,7 @@ def part3(): model=model, device_name="AUTO", config={ - ov.properties.hint.performance_mode(): ov.properties.hint.PerformanceMode.THROUGHPUT + hints.performance_mode(): hints.PerformanceMode.THROUGHPUT }, ) # To use the “LATENCY” mode: @@ -81,7 +89,7 @@ def part3(): model=model, device_name="AUTO", config={ - ov.properties.hint.performance_mode(): ov.properties.hint.PerformanceMode.LATENCY + hints.performance_mode(): hints.PerformanceMode.LATENCY }, ) # To use the “CUMULATIVE_THROUGHPUT” mode: @@ -89,7 +97,7 @@ def part3(): model=model, device_name="AUTO", config={ - ov.properties.hint.performance_mode(): ov.properties.hint.PerformanceMode.CUMULATIVE_THROUGHPUT + hints.performance_mode(): hints.PerformanceMode.CUMULATIVE_THROUGHPUT }, ) #! [part3] @@ -103,19 +111,19 @@ def part4(): compiled_model0 = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.hint.model_priority(): ov.properties.hint.Priority.HIGH}, + config={hints.model_priority(): hints.Priority.HIGH}, ) compiled_model1 = core.compile_model( model=model, device_name="AUTO", config={ - ov.properties.hint.model_priority(): ov.properties.hint.Priority.MEDIUM + hints.model_priority(): hints.Priority.MEDIUM }, ) compiled_model2 = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.hint.model_priority(): ov.properties.hint.Priority.LOW}, + config={hints.model_priority(): hints.Priority.LOW}, ) # Assume that all the devices (CPU and GPUs) can support all the networks. # Result: compiled_model0 will use GPU.1, compiled_model1 will use GPU.0, compiled_model2 will use CPU. @@ -124,19 +132,19 @@ def part4(): compiled_model3 = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.hint.model_priority(): ov.properties.hint.Priority.HIGH}, + config={hints.model_priority(): hints.Priority.HIGH}, ) compiled_model4 = core.compile_model( model=model, device_name="AUTO", config={ - ov.properties.hint.model_priority(): ov.properties.hint.Priority.MEDIUM + hints.model_priority(): hints.Priority.MEDIUM }, ) compiled_model5 = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.hint.model_priority(): ov.properties.hint.Priority.LOW}, + config={hints.model_priority(): hints.Priority.LOW}, ) # Assume that all the devices (CPU ang GPUs) can support all the networks. # Result: compiled_model3 will use GPU.1, compiled_model4 will use GPU.1, compiled_model5 will use GPU.0. @@ -161,12 +169,12 @@ def part6(): compiled_model = core.compile_model( model=model, device_name="AUTO", - config={ov.properties.log.level(): ov.properties.log.Level.DEBUG}, + config={log.level(): log.Level.DEBUG}, ) # set log level with set_property and compile model core.set_property( device_name="AUTO", - properties={ov.properties.log.level(): ov.properties.log.Level.DEBUG}, + properties={log.level(): log.Level.DEBUG}, ) compiled_model = core.compile_model(model=model, device_name="AUTO") #! [part6] @@ -179,7 +187,7 @@ def part7(): # compile a model on AUTO and set log level to debug compiled_model = core.compile_model(model=model, device_name="AUTO") # query the runtime target devices on which the inferences are being executed - execution_devices = compiled_model.get_property(ov.properties.execution_devices()) + execution_devices = compiled_model.get_property(properties.execution_devices()) #! [part7] diff --git a/docs/snippets/ov_auto_batching.py b/docs/snippets/ov_auto_batching.py index 5e4f3032f7d05f..7508c90337c240 100644 --- a/docs/snippets/ov_auto_batching.py +++ b/docs/snippets/ov_auto_batching.py @@ -15,8 +15,8 @@ def main(): return 0 # [compile_model] - import openvino.runtime.properties as props - import openvino.runtime.properties.hint as hints + import openvino.properties as props + import openvino.properties.hint as hints config = {hints.performance_mode(): hints.PerformanceMode.THROUGHPUT} compiled_model = core.compile_model(model, "GPU", config) diff --git a/docs/snippets/ov_caching.py b/docs/snippets/ov_caching.py index ef3fd0b4861ae6..87d9907a8b9106 100644 --- a/docs/snippets/ov_caching.py +++ b/docs/snippets/ov_caching.py @@ -5,7 +5,7 @@ from utils import get_path_to_model, get_temp_dir import openvino as ov -import openvino.runtime.properties as props +import openvino.properties as props device_name = 'GNA' model_path = get_path_to_model() @@ -35,6 +35,8 @@ assert compiled_model # ! [ov:caching:part3] +import openvino.properties.device as device + # Find 'EXPORT_IMPORT' capability in supported capabilities -caching_supported = 'EXPORT_IMPORT' in core.get_property(device_name, props.device.capabilities()) +caching_supported = 'EXPORT_IMPORT' in core.get_property(device_name, device.capabilities()) # ! [ov:caching:part3] diff --git a/docs/snippets/ov_denormals.py b/docs/snippets/ov_denormals.py index 45b77483fcc882..fe7cc8f797bc6c 100644 --- a/docs/snippets/ov_denormals.py +++ b/docs/snippets/ov_denormals.py @@ -9,8 +9,10 @@ model = get_model() # ! [ov:intel_cpu:denormals_optimization:part0] +import openvino.properties.intel_cpu as intel_cpu + core = ov.Core() -core.set_property("CPU", ov.properties.intel_cpu.denormals_optimization(True)) +core.set_property("CPU", intel_cpu.denormals_optimization(True)) compiled_model = core.compile_model(model=model, device_name=device_name) # ! [ov:intel_cpu:denormals_optimization:part0] assert compiled_model diff --git a/docs/snippets/ov_hetero.py b/docs/snippets/ov_hetero.py index 95623a1f74a14c..aa0eac7784fe4f 100644 --- a/docs/snippets/ov_hetero.py +++ b/docs/snippets/ov_hetero.py @@ -1,4 +1,5 @@ import openvino as ov +import openvino as properties from utils import get_model def main(): @@ -35,16 +36,20 @@ def main(): #! [fix_automatic_affinities] #! [compile_model] + import openvino.device as device + compiled_model = core.compile_model(model, device_name="HETERO:GPU,CPU") # device priorities via configuration property compiled_model = core.compile_model( - model, device_name="HETERO", config={ov.properties.device.priorities(): "GPU,CPU"} + model, device_name="HETERO", config={device.priorities(): "GPU,CPU"} ) #! [compile_model] #! [configure_fallback_devices] - core.set_property("HETERO", {ov.properties.device.priorities(): "GPU,CPU"}) - core.set_property("GPU", {ov.properties.enable_profiling(): True}) - core.set_property("CPU", {ov.properties.hint.inference_precision(): ov.Type.f32}) + import openvino.hint as hints + + core.set_property("HETERO", {device.priorities(): "GPU,CPU"}) + core.set_property("GPU", {properties.enable_profiling(): True}) + core.set_property("CPU", {hints.inference_precision(): ov.Type.f32}) compiled_model = core.compile_model(model=model, device_name="HETERO") #! [configure_fallback_devices] diff --git a/docs/snippets/ov_multi.py b/docs/snippets/ov_multi.py index 19ec07d8f9a8c5..bae82aa3d47713 100644 --- a/docs/snippets/ov_multi.py +++ b/docs/snippets/ov_multi.py @@ -1,5 +1,9 @@ -import sys +# Copyright (C) 2018-2023 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + import openvino as ov +import openvino.properties as properties +import openvino.properties.device as device from utils import get_model model = get_model() @@ -13,7 +17,7 @@ def MULTI_0(): # Pre-configure MULTI globally with explicitly defined devices, # and compile the model on MULTI using the newly specified default device list. core.set_property( - device_name="MULTI", properties={ov.properties.device.priorities(): "GPU,CPU"} + device_name="MULTI", properties={device.priorities(): "GPU,CPU"} ) compiled_model = core.compile_model(model=model, device_name="MULTI") @@ -24,7 +28,7 @@ def MULTI_0(): compiled_model = core.compile_model( model=model, device_name="MULTI", - config={ov.properties.device.priorities(): "GPU,CPU"}, + config={device.priorities(): "GPU,CPU"}, ) #! [MULTI_0] @@ -34,22 +38,22 @@ def MULTI_1(): core = ov.Core() core.set_property( - device_name="MULTI", properties={ov.properties.device.priorities(): "CPU,GPU"} + device_name="MULTI", properties={device.priorities(): "CPU,GPU"} ) # Once the priority list is set, you can alter it on the fly: # reverse the order of priorities core.set_property( - device_name="MULTI", properties={ov.properties.device.priorities(): "GPU,CPU"} + device_name="MULTI", properties={device.priorities(): "GPU,CPU"} ) # exclude some devices (in this case, CPU) core.set_property( - device_name="MULTI", properties={ov.properties.device.priorities(): "GPU"} + device_name="MULTI", properties={device.priorities(): "GPU"} ) # bring back the excluded devices core.set_property( - device_name="MULTI", properties={ov.properties.device.priorities(): "GPU,CPU"} + device_name="MULTI", properties={device.priorities(): "GPU,CPU"} ) # You cannot add new devices on the fly! @@ -105,7 +109,7 @@ def MULTI_4(): # Optionally, query the optimal number of requests: nireq = compiled_model.get_property( - ov.properties.optimal_number_of_infer_requests() + properties.optimal_number_of_infer_requests() ) #! [MULTI_4] diff --git a/docs/snippets/ov_properties_api.py b/docs/snippets/ov_properties_api.py index cc9645a7682e92..369e88ad572de3 100644 --- a/docs/snippets/ov_properties_api.py +++ b/docs/snippets/ov_properties_api.py @@ -3,8 +3,9 @@ # import openvino as ov -import openvino.runtime.properties as props -import openvino.runtime.properties.hint as hints +import openvino.properties as props +import openvino.properties.hint as hints +import openvino.properties.device as device from utils import get_model @@ -16,11 +17,11 @@ def main(): # [get_available_devices] # [hetero_priorities] - device_priorites = core.get_property("HETERO", props.device.priorities()) + device_priorites = core.get_property("HETERO", device.priorities()) # [hetero_priorities] # [cpu_device_name] - cpu_device_name = core.get_property("CPU", props.device.full_name()) + cpu_device_name = core.get_property("CPU", device.full_name()) # [cpu_device_name] model = get_model() @@ -56,8 +57,8 @@ def main(): return 0 # [multi_device] - config = {props.device.priorities(): "CPU,GPU"} + config = {device.priorities(): "CPU,GPU"} compiled_model = core.compile_model(model, "MULTI", config) # change the order of priorities - compiled_model.set_property({props.device.priorities(): "GPU,CPU"}) + compiled_model.set_property({device.priorities(): "GPU,CPU"}) # [multi_device] diff --git a/docs/snippets/ov_properties_migration.py b/docs/snippets/ov_properties_migration.py index a590e3053e8312..88addb6a72d925 100644 --- a/docs/snippets/ov_properties_migration.py +++ b/docs/snippets/ov_properties_migration.py @@ -3,8 +3,10 @@ # import openvino as ov -import openvino.runtime.properties as props -import openvino.runtime.properties.hint as hints +import openvino.properties as props +import openvino.properties.hint as hints +import openvino.properties.device as device +import openvino.properties.streams as streams from utils import get_model @@ -23,7 +25,7 @@ def main(): # ! [core_compile_model] compiled_model = core.compile_model(model=model, device_name="MULTI", config= { - props.device.priorities(): "GPU,CPU", + device.priorities(): "GPU,CPU", hints.performance_mode(): hints.PerformanceMode.THROUGHPUT, hints.inference_precision(): ov.Type.f32 }) @@ -31,15 +33,15 @@ def main(): # ! [compiled_model_set_property] # turn CPU off for multi-device execution - compiled_model.set_property(properties={props.device.priorities(): "GPU"}) + compiled_model.set_property(properties={device.priorities(): "GPU"}) # ! [compiled_model_set_property] # ! [core_get_rw_property] - num_streams = core.get_property("CPU", props.streams.num()) + num_streams = core.get_property("CPU", streams.num()) # ! [core_get_rw_property] # ! [core_get_ro_property] - full_device_name = core.get_property("CPU", props.device.full_name()) + full_device_name = core.get_property("CPU", device.full_name()) # ! [core_get_ro_property] # ! [compiled_model_get_rw_property] From e090e37f6f0f865c8298acf7a19b7ebb84e677ff Mon Sep 17 00:00:00 2001 From: Andrey Kashchikhin Date: Fri, 15 Sep 2023 13:24:44 +0100 Subject: [PATCH 10/12] [CI] [GHA] Introduce GHA Linux Conditional Compilation Pipeline (#19341) * introduce linux cc * disable some triggers * check dirs * use another model * return model * rm triggers --------- Co-authored-by: Mikhail Ryzhov --- .../linux_conditional_compilation.yml | 142 ++++++++++++++++++ 1 file changed, 142 insertions(+) create mode 100644 .github/workflows/linux_conditional_compilation.yml diff --git a/.github/workflows/linux_conditional_compilation.yml b/.github/workflows/linux_conditional_compilation.yml new file mode 100644 index 00000000000000..5522dce84e9c52 --- /dev/null +++ b/.github/workflows/linux_conditional_compilation.yml @@ -0,0 +1,142 @@ +name: Linux Conditional Compilation (Ubuntu 22.04, 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-cc + 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-latest-8-cores + env: + CMAKE_BUILD_TYPE: 'Release' + CMAKE_GENERATOR: 'Ninja' + CMAKE_CXX_COMPILER_LAUNCHER: ccache + CMAKE_C_COMPILER_LAUNCHER: ccache + OPENVINO_REPO: ${{ github.workspace }}/openvino + OPENVINO_CONTRIB_REPO: ${{ github.workspace }}/openvino_contrib + BUILD_DIR: ${{ github.workspace }}/build + DATA_PATH: ${{ github.workspace }}/testdata + MODELS_PATH: ${{ github.workspace }}/testdata + OV_TEMP: ${{ github.workspace }}/openvino_temp + PYTHON_STATIC_ARGS: -m "not dynamic_library and not template_plugin" + steps: + - name: Clone OpenVINO + uses: actions/checkout@v3 + with: + path: 'openvino' + submodules: 'recursive' + + - name: Clone testdata for C API tests + uses: actions/checkout@v3 + with: + repository: 'openvinotoolkit/testdata' + path: 'testdata' + submodules: 'recursive' + lfs: 'true' + + # + # Dependencies + # + + - name: Install build dependencies + run: | + sudo -E ${{ env.OPENVINO_REPO }}/install_build_dependencies.sh + sudo -E apt update + sudo -E apt --assume-yes install openjdk-11-jdk libbz2-dev clang unzip libpugixml-dev libtbb-dev intel-opencl-icd ocl-icd-opencl-dev opencl-headers + + wget https://github.com/ninja-build/ninja/releases/download/v1.10.2/ninja-linux.zip + unzip ninja-linux.zip + sudo cp -v ninja /usr/local/bin/ + + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + + # + # Build + # + + - 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: linux-cc + restore-keys: | + linux-cc + + - name: Get number of CPU cores + uses: SimenB/github-actions-cpu-cores@v2 + id: cpu-cores + + - name: CMake configure CC COLLECT + run: | + cmake \ + -G "Ninja Multi-Config" \ + -DENABLE_CPPLINT=OFF \ + -DENABLE_GAPI_PREPROCESSING=OFF \ + -DCMAKE_VERBOSE_MAKEFILE=ON \ + -DCMAKE_COMPILE_WARNING_AS_ERROR=OFF \ + -DENABLE_FASTER_BUILD=ON \ + -DENABLE_PROFILING_ITT=ON \ + -DSELECTIVE_BUILD=COLLECT \ + -S ${{ env.OPENVINO_REPO }} \ + -B ${{ env.BUILD_DIR }} + + - name: Clean ccache stats + run: ccache --zero-stats --show-config + + - name: Build CC COLLECT + run: cmake --build ${{ env.BUILD_DIR }} --parallel ${{ steps.cpu-cores.outputs.count }} --config Release --target openvino_intel_cpu_plugin openvino_ir_frontend benchmark_app sea_itt_lib + + - name: Show ccache stats + run: ccache --show-stats + + - name: Code usage analysis + run: | + python3 ${{ env.OPENVINO_REPO }}/thirdparty/itt_collector/runtool/sea_runtool.py \ + --bindir ${{ env.OPENVINO_REPO }}/bin/intel64/Release -o ${{ env.BUILD_DIR }}/itt_stat ! \ + ${{ env.OPENVINO_REPO }}/bin/intel64/Release/benchmark_app -niter 1 -nireq 1 \ + -m ${{ env.MODELS_PATH }}/models/test_model/test_model_fp32.xml -d CPU + + - name: CMake configure with CC ON + run: cmake -DSELECTIVE_BUILD=ON -DSELECTIVE_BUILD_STAT=${{ env.BUILD_DIR }}/*.csv -S ${{ env.OPENVINO_REPO }} -B ${{ env.BUILD_DIR }} + + - name: Build with CC ON + run: cmake --build ${{ env.BUILD_DIR }} --parallel ${{ steps.cpu-cores.outputs.count }} --config Release --target openvino_intel_cpu_plugin openvino_ir_frontend + + - name: Use OpenVINO after CC + run: | + ${{ env.OPENVINO_REPO }}/bin/intel64/Release/benchmark_app -niter 1 -nireq 1 \ + -m ${{ env.MODELS_PATH }}/models/test_model/test_model_fp32.xml -d CPU From 2cd130810432662f9974521e76418d876ef470e1 Mon Sep 17 00:00:00 2001 From: Andrey Kashchikhin Date: Fri, 15 Sep 2023 13:25:32 +0100 Subject: [PATCH 11/12] [CI] [GHA] Introduce GHA Windows Conditional Compilation Pipeline (#19343) * introduce win cc pipeline * disable some triggers * do not install unnecessary dependencies * clone models * rm triggers --------- Co-authored-by: Mikhail Ryzhov --- .../windows_conditional_compilation.yml | 170 ++++++++++++++++++ 1 file changed, 170 insertions(+) create mode 100644 .github/workflows/windows_conditional_compilation.yml diff --git a/.github/workflows/windows_conditional_compilation.yml b/.github/workflows/windows_conditional_compilation.yml new file mode 100644 index 00000000000000..94c4ec773c268f --- /dev/null +++ b/.github/workflows/windows_conditional_compilation.yml @@ -0,0 +1,170 @@ +name: Tests on Windows Conditional Compilation (VS 2022, 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: ${{ github.head_ref || github.run_id }}-windows-cc + cancel-in-progress: true + +env: + CMAKE_BUILD_TYPE: 'Release' + CMAKE_GENERATOR: 'Ninja' + CMAKE_CXX_COMPILER_LAUNCHER: sccache + CMAKE_C_COMPILER_LAUNCHER: sccache + OPENVINO_REPO: "${{ github.workspace }}\\openvino" + OPENVINO_CONTRIB_REPO: "${{ github.workspace }}\\openvino_contrib" + INSTALL_DIR: "${{ github.workspace }}\\install_pkg" + INSTALL_TEST_DIR: "${{ github.workspace }}\\install\\tests" + SAMPLES_INSTALL_DIR: "${{ github.workspace }}\\install\\samples" + LAYER_TESTS_INSTALL_DIR: "${{ github.workspace }}\\install\\tests\\layer_tests" + BUILD_DIR: "${{ github.workspace }}\\build" + BUILD_DIR_2: "${{ github.workspace }}\\build_s" + DATA_PATH: "${{ github.workspace }}\\testdata" + MODELS_PATH: "${{ github.workspace }}\\testdata" + OV_TEMP: "${{ github.workspace }}\\openvino_temp" + BUILD_TYPE: "Release" + PYTHON_STATIC_ARGS: -m "not dynamic_library and not template_plugin" + VCVARSPATH: "C:\\Program Files\\Microsoft Visual Studio\\2022\\Enterprise\\VC\\Auxiliary\\Build\\vcvarsall.bat" + +jobs: + Build: + # TODO: remove. Temporary measure to prevent the workflow from scheduling on forks. + if: ${{ github.repository_owner == 'openvinotoolkit' }} + defaults: + run: + shell: pwsh + runs-on: windows-latest-8-cores + steps: + - name: Clone OpenVINO + uses: actions/checkout@v3 + with: + path: 'openvino' + submodules: 'recursive' + + - name: Clone testdata for sample test + uses: actions/checkout@v4 + with: + repository: 'openvinotoolkit/testdata' + path: 'testdata' + submodules: 'recursive' + lfs: 'true' + + # + # Dependencies + # + + - uses: actions/setup-python@v4 + with: + python-version: '3.11' + + - name: Install build dependencies + run: | + choco install --no-progress ninja + + # + # Build + # + + - name: Get number of CPU cores + uses: SimenB/github-actions-cpu-cores@v1 + id: cpu-cores + + - uses: ilammy/msvc-dev-cmd@v1 + + - name: Setup sccache + uses: hendrikmuhs/ccache-action@v1.2 + with: + variant: sccache + 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' }} + key: ${{ github.job }}-windows-cc + restore-keys: | + ${{ github.job }}-windows-cc + + - name: CMake CC COLLECT + run: | + & "${{ env.VCVARSPATH }}" x64 && cmake -G Ninja ` + -DENABLE_CPPLINT=OFF ` + -DENABLE_GAPI_PREPROCESSING=OFF ` + -DENABLE_PLUGINS_XML=ON ` + -DCMAKE_COMPILE_WARNING_AS_ERROR=OFF ` + -DCMAKE_BUILD_TYPE=${{ env.BUILD_TYPE }} ` + -DENABLE_PROFILING_ITT=ON ` + -DSELECTIVE_BUILD=COLLECT ` + -S ${{ env.OPENVINO_REPO }} ` + -B ${{ env.BUILD_DIR }} + + - name: Build CC COLLECT + run: | + & "${{ env.VCVARSPATH }}" x64 && cmake --build ${{ env.BUILD_DIR }} --parallel ${{ steps.cpu-cores.outputs.count }} --config ${{ env.BUILD_TYPE }} ` + --target openvino_intel_cpu_plugin openvino_ir_frontend benchmark_app sea_itt_lib + + - name: List bin files + shell: cmd + run: dir ${{ env.OPENVINO_REPO }}\bin\ /s + + - name: Code usage analysis + shell: cmd + working-directory: ${{ env.OPENVINO_REPO }} + run: | + set path=%path%;${{ env.OPENVINO_REPO }}\temp\tbb\bin + call "${{ env.VCVARSPATH }}" && python thirdparty\itt_collector\runtool\sea_runtool.py --bindir ${{ env.OPENVINO_REPO }}\bin\intel64\${{ env.BUILD_TYPE }} -o ${{ env.BUILD_DIR }}\itt_stat ! ${{ env.OPENVINO_REPO }}\bin\intel64\${{ env.BUILD_TYPE }}\benchmark_app.exe -niter 1 -nireq 1 -m ${{ env.MODELS_PATH }}\models\test_model\test_model_fp32.xml -d CPU + + - name: List csv files + shell: cmd + run: dir ${{ env.BUILD_DIR }}\*.csv /s /p + + - name: CMake CC ON + run: | + & "${{ env.VCVARSPATH }}" x64 && cmake -G "Visual Studio 17 2022" ` + -DVERBOSE_BUILD=ON ` + -DENABLE_CPPLINT=OFF ` + -DENABLE_GAPI_PREPROCESSING=OFF ` + -DENABLE_PROFILING_ITT=OFF ` + -DSELECTIVE_BUILD=ON ` + -DCMAKE_COMPILE_WARNING_AS_ERROR=OFF ` + -DSELECTIVE_BUILD_STAT=${{ env.BUILD_DIR }}\*.csv ` + -S ${{ env.OPENVINO_REPO }} ` + -B ${{ env.BUILD_DIR_2 }} + + - name: Build CC ON + run: | + & "${{ env.VCVARSPATH }}" x64 && cmake --build ${{ env.BUILD_DIR_2 }} --parallel ${{ steps.cpu-cores.outputs.count }} --config ${{ env.BUILD_TYPE }} ` + --target openvino_intel_cpu_plugin openvino_ir_frontend benchmark_app + + - name: List bin files ON + shell: cmd + run: dir ${{ env.OPENVINO_REPO }}\bin\ /s + + - name: Check conditional_compilation_gen.h header + shell: cmd + run: type ${{ env.BUILD_DIR_2 }}\src\common\conditional_compilation\conditional_compilation_gen.h + + - name: Use OpenVINO after CC + shell: cmd + run: | + set path=%path%;${{ env.OPENVINO_REPO }}\temp\tbb\bin + ${{ env.OPENVINO_REPO }}\bin\intel64\${{ env.BUILD_TYPE }}\benchmark_app.exe -niter 1 -nireq 1 -m ${{ env.MODELS_PATH }}\models\test_model\test_model_fp32.xml -d CPU From bcb469ab192a713ac480c768acbd2a96ae00d9b5 Mon Sep 17 00:00:00 2001 From: Maciej Smyk Date: Fri, 15 Sep 2023 14:55:32 +0200 Subject: [PATCH 12/12] 19680 & 19849 (#19879) --- .../images/DEVELOPMENT_FLOW_V3_crunch.svg | 4 +- docs/_static/images/WHAT_TO_USE.svg | 4 +- .../model_optimization_guide.md | 6 ++- .../nncf/code/weight_compression_openvino.py | 6 +++ .../nncf/weight_compression.md | 37 +++++++++++++++++++ 5 files changed, 52 insertions(+), 5 deletions(-) create mode 100644 docs/optimization_guide/nncf/code/weight_compression_openvino.py create mode 100644 docs/optimization_guide/nncf/weight_compression.md diff --git a/docs/_static/images/DEVELOPMENT_FLOW_V3_crunch.svg b/docs/_static/images/DEVELOPMENT_FLOW_V3_crunch.svg index 99023d14b6c4b1..c183f387509c1c 100644 --- a/docs/_static/images/DEVELOPMENT_FLOW_V3_crunch.svg +++ b/docs/_static/images/DEVELOPMENT_FLOW_V3_crunch.svg @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:d02f98d7e50d663e0f525366b59cac16175ad437ee54147950a62b9bccb85030 -size 413331 +oid sha256:3ea9a60d2b9a1f3056f46b995f9cf5fee83d04e57ada60c60ed7661ab09d08c7 +size 367000 diff --git a/docs/_static/images/WHAT_TO_USE.svg b/docs/_static/images/WHAT_TO_USE.svg index 5a87c4558221db..5cba27ea4ee0eb 100644 --- a/docs/_static/images/WHAT_TO_USE.svg +++ b/docs/_static/images/WHAT_TO_USE.svg @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:b71a90fd9ec78356eef5ef0c9d80831c1439fbfc05d42fc0ad648f4b5aa151aa -size 286982 +oid sha256:2a30e182191979bf0693d9060eee2596313e162042f68bce31859670e21ad0c4 +size 206149 diff --git a/docs/optimization_guide/model_optimization_guide.md b/docs/optimization_guide/model_optimization_guide.md index 718fd5310aaea3..02963573151d89 100644 --- a/docs/optimization_guide/model_optimization_guide.md +++ b/docs/optimization_guide/model_optimization_guide.md @@ -8,6 +8,7 @@ ptq_introduction tmo_introduction + weight_compression Model optimization is an optional offline step of improving the final model performance and reducing the model size by applying special optimization methods, such as 8-bit quantization, pruning, etc. OpenVINO offers two optimization paths implemented in `Neural Network Compression Framework (NNCF) `__: @@ -16,9 +17,11 @@ Model optimization is an optional offline step of improving the final model perf - :doc:`Training-time Optimization `, a suite of advanced methods for training-time model optimization within the DL framework, such as PyTorch and TensorFlow 2.x. It supports methods like Quantization-aware Training, Structured and Unstructured Pruning, etc. +- :doc:`Weight Compression `, an easy-to-use method for Large Language Models footprint reduction and inference acceleration. + .. note:: OpenVINO also supports optimized models (for example, quantized) from source frameworks such as PyTorch, TensorFlow, and ONNX (in Q/DQ; Quantize/DeQuantize format). No special steps are required in this case and optimized models can be converted to the OpenVINO Intermediate Representation format (IR) right away. -Post-training Quantization is the fastest way to optimize a model and should be applied first, but it is limited in terms of achievable accuracy-performance trade-off. The recommended approach to obtain OpenVINO quantized model is to convert a model from original framework to ``ov.Model`` and ensure that the model works correctly in OpenVINO, for example, by calculating the model metrics. Then, ``ov.Model`` can be used as input for the ``nncf.quantize()`` method to get the quantized model (see the diagram below). +Post-training Quantization is the fastest way to optimize an arbitrary DL model and should be applied first, but it is limited in terms of achievable accuracy-performance trade-off. The recommended approach to obtain OpenVINO quantized model is to convert a model from original framework to ``ov.Model`` and ensure that the model works correctly in OpenVINO, for example, by calculating the model metrics. Then, ``ov.Model`` can be used as input for the ``nncf.quantize()`` method to get the quantized model (see the diagram below). In case of unsatisfactory accuracy or performance after Post-training Quantization, Training-time Optimization can be used as an option. @@ -33,6 +36,7 @@ Additional Resources - :doc:`Post-training Quantization ` - :doc:`Training-time Optimization ` +- :doc:`Weight Compression ` - :doc:`Deployment optimization ` - `HuggingFace Optimum Intel `__ diff --git a/docs/optimization_guide/nncf/code/weight_compression_openvino.py b/docs/optimization_guide/nncf/code/weight_compression_openvino.py new file mode 100644 index 00000000000000..c9ab67efd5aa32 --- /dev/null +++ b/docs/optimization_guide/nncf/code/weight_compression_openvino.py @@ -0,0 +1,6 @@ +#! [compression_8bit] +from nncf import compress_weights + +... +model = compress_weights(model) # model is openvino.Model object +#! [compression_8bit] \ No newline at end of file diff --git a/docs/optimization_guide/nncf/weight_compression.md b/docs/optimization_guide/nncf/weight_compression.md new file mode 100644 index 00000000000000..efec4839d47a1f --- /dev/null +++ b/docs/optimization_guide/nncf/weight_compression.md @@ -0,0 +1,37 @@ +# Weight Compression {#weight_compression} + +@sphinxdirective + +Enhancing Model Efficiency with Weight Compression +################################################################## + +Weight compression aims to reduce the memory footprint of a model. It can also lead to significant performance improvement for large memory-bound models, such as Large Language Models (LLMs). LLMs and other models, which require extensive memory to store the weights during inference, can benefit from weight compression in the following ways: + +- enabling the inference of exceptionally large models that cannot be accommodated in the memory of the device; +- improving the inference performance of the models by reducing the latency of the memory access when computing the operations with weights, for example, Linear layers. + +Currently, NNCF provides 8-bit weight quantization as a compression method primarily designed to optimize LLMs. The main difference between weights compression and full model quantization (post-training quantization) is that activations remain floating-point in the case of weights compression which leads to a better accuracy. Weight compression for LLMs provides a solid inference performance improvement which is on par with the performance of the full model quantization. In addition, weight compression is data-free and does not require a calibration dataset, making it easy to use. + +Compress Model Weights +###################### + +The code snippet below shows how to compress the weights of the model represented in OpenVINO IR using NNCF: + +.. tab-set:: + + .. tab-item:: OpenVINO + :sync: openvino + + .. doxygensnippet:: docs/optimization_guide/nncf/code/weight_compression_openvino.py + :language: python + :fragment: [compression_8bit] + +Now, the model is ready for compilation and inference. It can be also saved into a compressed format, resulting in a smaller binary file. + +Additional Resources +#################### + +- :doc:`Post-training Quantization ` +- :doc:`Training-time Optimization ` + +@endsphinxdirective