[TF FE] Test TF Hugging Face models

.github/labeler.yml

@@ -142,7 +142,7 @@
 - 'tests/layer_tests/tensorflow2_keras_tests/**/*'
 - 'tests/layer_tests/jax_tests/**/*'
 - any: ['tests/model_hub_tests/**',
-        '!tests/model_hub_tests/torch_tests/**/*']
+        '!tests/model_hub_tests/tf_tests/**/*']
 
 'category: TFL FE':
 - 'src/frontends/tensorflow_lite/**/*'
@@ -156,7 +156,7 @@
 - 'tests/layer_tests/py_frontend_tests/test_torch_decoder.py'
 - 'tests/layer_tests/py_frontend_tests/test_torch_frontend.py'
 - any: ['tests/model_hub_tests/**',
-        '!tests/model_hub_tests/tf_hub_tests/**/*']
+        '!tests/model_hub_tests/torch_tests/**/*']
 
 'category: tools':
 - any: ['tools/**',

.github/workflows/job_tensorflow_hub_models_tests.yml

@@ -1,4 +1,4 @@
-name: TensorFlow Hub Models tests
+name: TensorFlow Models tests
 
 on:
   workflow_call:
@@ -108,12 +108,28 @@ jobs:
           python3 -m pip install ${INSTALL_DIR}/openvino_tokenizers-*
 
       - name: Install TF Hub tests requirements
-        run: python3 -m pip install -r ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_hub_tests/requirements.txt
+        run: python3 -m pip install -r ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_tests/requirements.txt
 
       - name: TensorFlow Hub Tests - TF FE
         run: |
           export PYTHONPATH=${MODEL_HUB_TESTS_INSTALL_DIR}:$PYTHONPATH
-          python3 -m pytest ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_hub_tests/ -m ${TYPE} --html=${INSTALL_TEST_DIR}/TEST-tf_hub_tf_fe.html --self-contained-html -v
+          python3 -m pytest ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_tests/ -m ${TYPE} --html=${INSTALL_TEST_DIR}/TEST-tf_hub_tf_fe.html --self-contained-html -v --scope tf_hub
+        env:
+          TYPE: ${{ inputs.event == 'schedule' && 'nightly' || 'precommit'}}
+          TEST_DEVICE: CPU
+
+      - name: TensorFlow Hugging Face Tests - TF FE
+        run: |
+          export PYTHONPATH=${MODEL_HUB_TESTS_INSTALL_DIR}:$PYTHONPATH
+          python3 -m pytest ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_tests/test_tf_convert_model.py -m ${TYPE} --html=${INSTALL_TEST_DIR}/TEST-tf_hub_tf_fe.html --self-contained-html -v --scope hf
+        env:
+          TYPE: ${{ inputs.event == 'schedule' && 'nightly' || 'precommit'}}
+          TEST_DEVICE: CPU
+
+      - name: TensorFlow Other Tests (OMZ) - TF FE
+        run: |
+          export PYTHONPATH=${MODEL_HUB_TESTS_INSTALL_DIR}:$PYTHONPATH
+          python3 -m pytest ${MODEL_HUB_TESTS_INSTALL_DIR}/tf_tests/test_tf_convert_model.py -m ${TYPE} --html=${INSTALL_TEST_DIR}/TEST-tf_hub_tf_fe.html --self-contained-html -v --scope others
         env:
           TYPE: ${{ inputs.event == 'schedule' && 'nightly' || 'precommit'}}
           TEST_DEVICE: CPU

src/bindings/python/src/openvino/frontend/tensorflow/utils.py

@@ -151,13 +151,28 @@ def get_concrete_func(tf_function, example_input, input_needs_packing, error_mes
     return concrete_func
 
 
+def get_signature_from_input(keras_model):
+    if not hasattr(keras_model, 'input') or getattr(keras_model, 'input') is None:
+        return None
+    return getattr(keras_model, 'input')
+
+
+def get_signature_from_input_signature(keras_model):
+    if not hasattr(keras_model, 'input_signature') or getattr(keras_model, 'input_signature') is None:
+        return None
+    return getattr(keras_model, 'input_signature')
+
+
 def create_generic_function_from_keras_model(keras_model):
     import tensorflow as tf
-    assert isinstance(keras_model, tf.keras.Model), \
-        "[TensorFlow Frontend] internal error: the input model must be of Keras model type"
-    if not hasattr(keras_model, 'input') or getattr(keras_model, 'input') is None:
+    assert isinstance(keras_model, (tf.keras.Model, tf.Module)), \
+        "[TensorFlow Frontend] internal error: the input model must be of tf.keras.Model or tf.Module model type"
+
+    keras_input_signature = get_signature_from_input(keras_model)
+    if keras_input_signature is None:
+        keras_input_signature = get_signature_from_input_signature(keras_model)
+    if keras_input_signature is None:
         return None
-    keras_input_signature = getattr(keras_model, 'input')
     tf_input_signature = None
     wrapper_function = None
     if isinstance(keras_input_signature, dict):
@@ -218,7 +233,7 @@ def trace_tf_model(model, input_shapes, input_types, example_input):
     elif isinstance(model, tf.types.experimental.GenericFunction):
         tf_function = model
         input_needs_packing = False
-    elif isinstance(model, tf.keras.Model):
+    elif isinstance(model, (tf.keras.Model, tf.Module)):
         tf_function = create_generic_function_from_keras_model(model)
         if tf_function is not None:
             input_needs_packing = False
@@ -370,7 +385,7 @@ def extract_model_graph(argv):
         argv["input_model"] = model.graph
         return True
     if Version(env_setup["tensorflow"]) >= parse("2.6.0") and isinstance(model, (tf.types.experimental.GenericFunction,
-                                                                               tf.types.experimental.ConcreteFunction)):
+                                                                                 tf.types.experimental.ConcreteFunction)):
         return True
     if isinstance(model, tf.train.Checkpoint):
         if isinstance(model.root, tf.keras.Model):

tests/model_hub_tests/models_hub_common/utils.py

@@ -5,12 +5,21 @@
 import os
 import shutil
 import time
+import sys
 
 import numpy as np
 from models_hub_common.constants import test_device
 
+def is_tf_hub_link(link: str):
+    return "www.kaggle.com" in link or "tfhub.dev" in link
+
+def is_hf_link(link: str):
+    return link.startswith("hf_")
 
 def get_models_list(file_name: str):
+    scope = "all"
+    if "--scope" in sys.argv and len(sys.argv) >= sys.argv.index("--scope") + 1:
+        scope = sys.argv[sys.argv.index("--scope") + 1]
     models = []
     with open(file_name) as f:
         for model_info in f:
@@ -20,14 +29,27 @@ def get_models_list(file_name: str):
                 continue
             mark = None
             reason = None
+            model_link = None
             assert len(model_info.split(',')) == 2 or len(model_info.split(',')) == 4, \
                 "Incorrect model info `{}`. It must contain either 2 or 4 fields.".format(model_info)
             if len(model_info.split(',')) == 2:
                 model_name, model_link = model_info.split(',')
             elif len(model_info.split(',')) == 4:
                 model_name, model_link, mark, reason = model_info.split(',')
                 assert mark in ["skip", "xfail"], "Incorrect failure mark for model info {}".format(model_info)
-            models.append((model_name, model_link, mark, reason))
+            if scope == "all":
+                models.append((model_name, model_link, mark, reason))
+            elif scope == "hf":
+                if is_hf_link(model_link):
+                    models.append((model_name, model_link, mark, reason))
+            elif scope == "tf_hub":
+                if is_tf_hub_link(model_link):
+                    models.append((model_name, model_link, mark, reason))
+            elif scope == "others":
+                if not is_hf_link(model_link) and not is_tf_hub_link(model_link):
+                    models.append((model_name, model_link, mark, reason))
+            else:
+                raise Exception("Unknown scope {}. Please select one of [all, hf, tf_hub, others].".format(scope))
 
     return models
 

tests/model_hub_tests/tf_tests/conftest.py

@@ -0,0 +1,27 @@
+# Copyright (C) 2018-2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import inspect
+
+import pytest
+
+from models_hub_common.utils import get_params
+
+
+def pytest_generate_tests(metafunc):
+    test_gen_attrs_names = list(inspect.signature(get_params).parameters)
+    params = get_params()
+    metafunc.parametrize(test_gen_attrs_names, params, scope="function")
+
+def pytest_addoption(parser):
+    """Specify command-line options"""
+    parser.addoption(
+        "--scope",
+        default="all",
+        action="store",
+        help="Models scope for testing. Select one of [all, tf_hub, hf, others]. Default: all.")
+
+@pytest.fixture(scope="function")
+def models_scope(request):
+    """Fixture function for command-line option."""
+    return request.config.getoption('scope')