Add preliminary support of OpenVINO as Keras 3 backend

.github/workflows/actions.yml

@@ -16,7 +16,7 @@ jobs:
       fail-fast: false
       matrix:
         python-version: [3.9]
-        backend: [tensorflow, jax, torch, numpy]
+        backend: [tensorflow, jax, torch, numpy, openvino]
     name: Run tests
     runs-on: ubuntu-latest
     env:
@@ -66,7 +66,7 @@ jobs:
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: false
       - name: Test integrations
-        if: ${{ matrix.backend != 'numpy'}}
+        if: ${{ matrix.backend != 'numpy' && matrix.backend != 'openvino' }}
         run: |
           python integration_tests/import_test.py
           python integration_tests/numerical_test.py
@@ -84,7 +84,14 @@ jobs:
         run: |
           pytest integration_tests/torch_workflow_test.py
           python integration_tests/torch_custom_fit_test.py
+      - name: Test OpenVINO-specific integrations
+        if: ${{ matrix.backend == 'openvino' }}
+        run: |
+          python integration_tests/import_test.py
+          pytest keras --ignore keras/src/applications --cov=keras --cov-config=pyproject.toml -m openvino_backend
+          coverage xml --omit='keras/src/applications/*,keras/api' -o core-coverage.xml
       - name: Test with pytest
+        if: ${{ matrix.backend != 'openvino'}}
         run: |
           pytest keras --ignore keras/src/applications --cov=keras --cov-config=pyproject.toml
           coverage xml --omit='keras/src/applications/*,keras/api' -o core-coverage.xml

.github/workflows/config/openvino/keras.json

@@ -0,0 +1,6 @@
+{
+    "floatx": "float32",
+    "epsilon": 1e-07,
+    "backend": "openvino",
+    "image_data_format": "channels_last"
+}

conftest.py

@@ -22,12 +22,16 @@ def pytest_configure(config):
         "markers",
         "requires_trainable_backend: mark test for trainable backend only",
     )
+    config.addinivalue_line(
+        "markers",
+        "openvino_backend: mark test case supported by OpenVINO backend",
+    )
 
 
 def pytest_collection_modifyitems(config, items):
     requires_trainable_backend = pytest.mark.skipif(
-        backend() == "numpy",
-        reason="Trainer not implemented for NumPy backend.",
+        backend() == "numpy" or backend() == "openvino",
+        reason="Trainer not implemented for NumPy and OpenVINO backend.",
     )
     for item in items:
         if "requires_trainable_backend" in item.keywords:

integration_tests/import_test.py

@@ -12,6 +12,7 @@
         "--extra-index-url https://download.pytorch.org/whl/cpu ",
     ),
     "jax": ("jax[cpu]", ""),
+    "openvino": ("openvino", ""),
 }
 
 
@@ -57,18 +58,26 @@ def manage_venv_installs(whl_path):
         "pip uninstall -y "
         + BACKEND_REQ[other_backends[0]][0]
         + " "
-        + BACKEND_REQ[other_backends[1]][0],
+        + BACKEND_REQ[other_backends[1]][0]
+        + " "
+        + BACKEND_REQ[other_backends[2]][0],
         # Install `.whl` package
         "pip install " + whl_path,
     ]
     run_commands_venv(install_setup)
 
 
 def run_keras_flow():
-    test_script = [
-        # Runs the example script
-        "python -m pytest integration_tests/basic_full_flow.py",
-    ]
+    if backend.backend() == "openvino":
+        test_script = [
+            # Runs the example script
+            "python -m pytest integration_tests/openvino/basic_full_flow.py",
+        ]
+    else:
+        test_script = [
+            # Runs the example script
+            "python -m pytest integration_tests/basic_full_flow.py",
+        ]
     run_commands_venv(test_script)
 
 

integration_tests/openvino/basic_full_flow.py

@@ -0,0 +1,24 @@
+import numpy as np
+
+import keras
+from keras.src import testing
+
+
+class BasicFlowTest(testing.TestCase):
+    def test_basic_fit(self):
+        def get_expected_result(x1, x2):
+            z = x1 + x2
+            return 1.0 / (1.0 + np.exp(-z))
+
+        x1 = keras.Input(shape=(2,), dtype="float32")
+        x2 = keras.Input(shape=(2,), dtype="float32")
+        add = keras.layers.Add()([x1, x2])
+        sigmoid = keras.activations.sigmoid(add)
+        model = keras.Model(inputs=[x1, x2], outputs=sigmoid)
+
+        x = np.random.random((128, 4))
+        y = np.random.random((128, 4))
+
+        result = model.predict([x, y])
+        expected = get_expected_result(x, y)
+        self.assertAllClose(result, expected, rtol=1e-05)

keras/src/backend/__init__.py

@@ -49,6 +49,11 @@
     from keras.src.backend.numpy import *  # noqa: F403
     from keras.src.backend.numpy.core import Variable as BackendVariable
 
+    distribution_lib = None
+elif backend() == "openvino":
+    from keras.src.backend.openvino import *  # noqa: F403
+    from keras.src.backend.openvino.core import Variable as BackendVariable
+
     distribution_lib = None
 else:
     raise ValueError(f"Unable to import backend : {backend()}")

keras/src/backend/openvino/__init__.py

@@ -0,0 +1,24 @@
+from keras.src.backend.common.name_scope import name_scope
+from keras.src.backend.openvino import core
+from keras.src.backend.openvino import image
+from keras.src.backend.openvino import linalg
+from keras.src.backend.openvino import math
+from keras.src.backend.openvino import nn
+from keras.src.backend.openvino import numpy
+from keras.src.backend.openvino import random
+from keras.src.backend.openvino.core import IS_THREAD_SAFE
+from keras.src.backend.openvino.core import SUPPORTS_SPARSE_TENSORS
+from keras.src.backend.openvino.core import Variable
+from keras.src.backend.openvino.core import cast
+from keras.src.backend.openvino.core import compute_output_spec
+from keras.src.backend.openvino.core import cond
+from keras.src.backend.openvino.core import convert_to_numpy
+from keras.src.backend.openvino.core import convert_to_tensor
+from keras.src.backend.openvino.core import is_tensor
+from keras.src.backend.openvino.core import random_seed_dtype
+from keras.src.backend.openvino.core import shape
+from keras.src.backend.openvino.core import vectorized_map
+from keras.src.backend.openvino.rnn import cudnn_ok
+from keras.src.backend.openvino.rnn import gru
+from keras.src.backend.openvino.rnn import lstm
+from keras.src.backend.openvino.rnn import rnn