support GPT-2 & enable tests

Author: Mohamed-Ashraf273

.github/workflows/actions.yml

@@ -53,7 +53,7 @@ jobs:
           pip install --no-deps -e "." --progress-bar off
           if [[ "${{ matrix.backend }}" == "openvino" ]]; then
             pip uninstall -y keras
-            pip install git+https://github.com/keras-team/keras.git@master --upgrade --force-reinstall --progress-bar off
+            pip install git+https://github.com/Mohamed-Ashraf273/keras.git@gsoc2025 --upgrade --force-reinstall --progress-bar off
           fi
     - name: Pin Keras 3.5
       if: ${{ matrix.version == 'keras-3.5'}}
@@ -67,20 +67,17 @@ jobs:
         pip install keras-nightly --progress-bar off
     - name: Test with pytest
       run: |
-        if [[ "${{ matrix.backend }}" == "openvino" ]]; then
-          pytest keras_hub/src/models/gemma/gemma_causal_lm_test.py
+        if [ "${{ matrix.backend }}" == "openvino" ]; then
+          IGNORE_FILE="openvino_excluded_tests.txt"
+          IGNORE_ARGS=$(awk '{print "--ignore=" $0}' "$IGNORE_FILE")
         else
-          pytest keras_hub/
+          IGNORE_ARGS=""
         fi
+        pytest keras_hub/ $IGNORE_ARGS
     - name: Run integration tests
       run: |
         python pip_build.py --install
-        cd integration_tests
-        if [[ "${{ matrix.backend }}" == "openvino" ]]; then
-          pytest . --ignore=basic_usage_test.py -k "not NoTensorflow"
-        else
-          pytest . -k "not NoTensorflow"
-        fi
+        cd integration_tests && pytest . -k "not NoTensorflow"
     - name: Run no tensorflow integration test
       if: ${{ matrix.backend != 'tensorflow'}}
       run: |

conftest.py

@@ -2,6 +2,7 @@
 
 import keras
 import pytest
+from keras.src.backend import backend
 
 
 def pytest_addoption(parser):
@@ -70,6 +71,10 @@ def pytest_configure(config):
         "markers",
         "kaggle_key_required: mark test needing a kaggle key",
     )
+    config.addinivalue_line(
+        "markers",
+        "requires_trainable_backend: mark test for trainable backend only",
+    )
 
 
 def pytest_collection_modifyitems(config, items):
@@ -110,6 +115,44 @@ def pytest_collection_modifyitems(config, items):
         if "kaggle_key_required" in item.keywords:
             item.add_marker(kaggle_key_required)
 
+    openvino_skipped_tests = []
+    if backend() == "openvino":
+        from pathlib import Path
+
+        workspace_root = Path(__file__).resolve().parents[0]
+        file_path = workspace_root / "openvino_excluded_concrete_tests.txt"
+        with open(file_path, "r") as file:
+            openvino_skipped_tests = file.readlines()
+            # it is necessary to check if stripped line is not empty
+            # and exclude such lines
+            openvino_skipped_tests = [
+                line.strip() for line in openvino_skipped_tests if line.strip()
+            ]
+
+    requires_trainable_backend = pytest.mark.skipif(
+        backend() in ["openvino"],
+        reason="Trainer not implemented for OpenVINO backend.",
+    )
+
+    for item in items:
+        if "requires_trainable_backend" in item.keywords:
+            item.add_marker(requires_trainable_backend)
+        # also, skip concrete tests for openvino, listed in the special file
+        # this is more granular mechanism to exclude tests rather
+        # than using --ignore option
+        for skipped_test in openvino_skipped_tests:
+            if skipped_test in item.nodeid:
+                item.add_marker(
+                    skip_if_backend(
+                        "openvino",
+                        "Not supported operation by openvino backend",
+                    )
+                )
+
+
+def skip_if_backend(given_backend, reason):
+    return pytest.mark.skipif(backend() == given_backend, reason=reason)
+
 
 # Disable traceback filtering for quicker debugging of tests failures.
 keras.config.disable_traceback_filtering()

integration_tests/basic_usage_test.py

@@ -6,6 +6,7 @@
 import keras_hub
 
 
+@unittest.skip("Skip for non-trainable backends like OpenVINO")
 class BasicUsageTest(unittest.TestCase):
     def test_transformer(self):
         # Tokenize some inputs with a binary label.

keras_hub/src/layers/modeling/alibi_bias_test.py

@@ -1,4 +1,5 @@
 import keras
+import pytest
 from keras import ops
 from keras import random
 
@@ -7,6 +8,7 @@
 
 
 class AlibiBiasTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         alibi_bias_max = 8
         batch_size = 4

keras_hub/src/layers/modeling/anchor_generator_test.py

@@ -14,6 +14,7 @@
     reason="Bbox utils are not supported before keras < 3.8.0",
 )
 class AnchorGeneratorTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         images_shape = (8, 128, 128, 3)
         self.run_layer_test(

keras_hub/src/layers/modeling/cached_multi_head_attention_test.py

@@ -1,3 +1,4 @@
+import pytest
 from keras import ops
 from keras import random
 
@@ -8,6 +9,7 @@
 
 
 class CachedMultiHeadAttentionTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         self.run_layer_test(
             cls=CachedMultiHeadAttention,
@@ -75,6 +77,7 @@ def call(outputs, cache):
         self.assertAllClose(output, no_loop_outputs)
         self.assertAllClose(output_cache, no_loop_cache)
 
+    @pytest.mark.requires_trainable_backend
     def test_training_propagation(self):
         batch_size = 2
         seq_len = 5

keras_hub/src/layers/modeling/f_net_encoder_test.py

@@ -1,3 +1,4 @@
+import pytest
 from keras import ops
 from keras import random
 
@@ -6,6 +7,7 @@
 
 
 class FNetEncoderTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         self.run_layer_test(
             cls=FNetEncoder,
@@ -31,6 +33,7 @@ def test_value_error_when_invalid_kernel_initializer(self):
                 kernel_initializer="Invalid",
             )
 
+    @pytest.mark.requires_trainable_backend
     def test_training_propagation(self):
         x = random.uniform(shape=(2, 4, 6))
         layer = FNetEncoder(

keras_hub/src/layers/modeling/masked_lm_head_test.py

@@ -1,3 +1,4 @@
+import pytest
 from keras import random
 
 from keras_hub.src.layers.modeling.masked_lm_head import MaskedLMHead
@@ -8,6 +9,7 @@
 
 
 class MaskedLMHeadTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         self.run_layer_test(
             cls=MaskedLMHead,

keras_hub/src/layers/modeling/position_embedding.py

@@ -103,6 +103,11 @@ def call(self, inputs, start_index=0):
             (start_index, 0),
             (sequence_length, feature_length),
         )
+        if keras.config.backend() == "openvino":
+            # Reshape to ensure we have the correct 2D shape after slicing
+            position_embeddings = ops.reshape(
+                position_embeddings, (sequence_length, feature_length)
+            )
         return ops.broadcast_to(position_embeddings, shape)
 
     def compute_output_shape(self, input_shape):

keras_hub/src/layers/modeling/position_embedding_test.py

@@ -1,5 +1,6 @@
 import keras
 import numpy as np
+import pytest
 from keras import ops
 from keras import random
 
@@ -15,6 +16,7 @@ def custom_init(shape, dtype=None):
 
 
 class PositionEmbeddingTest(TestCase):
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors(self):
         self.run_layer_test(
             cls=PositionEmbedding,
@@ -26,6 +28,7 @@ def test_layer_behaviors(self):
             expected_num_trainable_weights=1,
         )
 
+    @pytest.mark.requires_trainable_backend
     def test_layer_behaviors_4d(self):
         self.run_layer_test(
             cls=PositionEmbedding,