Keras 3 tests

.github/workflows/actions.yml

@@ -11,13 +11,13 @@ permissions:
   contents: read
 
 jobs:
-  keras2:
-    name: Test the code with tf.keras
+  keras_2:
+    name: Test the code with Keras 2
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python 3.9
-      uses: actions/setup-python@v1
+      uses: actions/setup-python@v4
       with:
         python-version: 3.9
     - name: Get pip cache dir
@@ -34,7 +34,7 @@ jobs:
           ${{ runner.os }}-pip-
     - name: Install dependencies
       run: |
-        pip install tensorflow>=2.13.0
+        pip install tensorflow~=2.14
         pip install torch>=2.0.1+cpu
         pip install "jax[cpu]"
         pip install keras-core
@@ -44,17 +44,17 @@ jobs:
         TEST_CUSTOM_OPS: false
       run: |
         pytest keras_cv/ --ignore keras_cv/models/legacy/ --durations 0
-  multibackend:
-    name: Test the code with Keras Core
+  keras_3:
+    name: Test the code with Keras 3
     strategy:
       fail-fast: false
       matrix:
         backend: [tensorflow, jax, torch]
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python 3.9
-      uses: actions/setup-python@v1
+      uses: actions/setup-python@v4
       with:
         python-version: 3.9
     - name: Get pip cache dir
@@ -71,12 +71,11 @@ jobs:
           ${{ runner.os }}-pip-
     - name: Install dependencies
       run: |
-        pip install tensorflow>=2.13.0
+        pip install -e ".[tests]" --progress-bar off --upgrade
         pip install "jax[cpu]"
         pip install torch>=2.0.1+cpu
         pip install torchvision>=0.15.1
-        pip install keras-core
-        pip install -e ".[tests]" --progress-bar off --upgrade
+        pip install tf-nightly==2.16.0.dev20231103  # Pin a working nightly until rc0.
     - name: Test with pytest
       env:
         TEST_CUSTOM_OPS: false # TODO(ianstenbit): test custom ops, or figure out what our story is here
@@ -99,9 +98,9 @@ jobs:
     name: Check the code format
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python 3.9
-      uses: actions/setup-python@v1
+      uses: actions/setup-python@v4
       with:
         python-version: 3.9
     - name: Get pip cache dir
@@ -118,7 +117,7 @@ jobs:
           ${{ runner.os }}-pip-
     - name: Install dependencies
       run: |
-        pip install tensorflow>=2.13.0
+        pip install tensorflow~=2.14
         pip install -e ".[tests]" --progress-bar off --upgrade
     - name: Lint
       run: bash shell/lint.sh
@@ -128,4 +127,4 @@ jobs:
         source: '.'
         extensions: 'h,c,cpp,hpp,cc'
         clangFormatVersion: 14
-        style: google
+        style: google

.github/workflows/devcontainer.yml

@@ -20,7 +20,7 @@ jobs:
     steps:
 
       - name: Checkout (GitHub)
-        uses: actions/checkout@v2
+        uses: actions/checkout@v4
 
       - name: Build and run dev container task
         uses: devcontainers/[email protected]

.github/workflows/nightly.yml

@@ -40,6 +40,7 @@ jobs:
           pip install -r requirements.txt --progress-bar off
       - name: Build wheel file
         run: |
+          export BUILD_WITH_CUSTOM_OPS=false
           python pip_build.py --nightly
       - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1

.github/workflows/release.yml

@@ -8,105 +8,38 @@ permissions:
   contents: read
 
 jobs:
-  deploy-with-custom-ops:
-    # This job is currently skipped until we cut a release with custom ops.
-    if: false
-    name: Build and deploy release wheels with custom ops
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        # To switch on windows-2022/latest, please verify the bazel version:
-        # https://github.com/bazelbuild/bazel/issues/14232#issuecomment-1011247429
-        os: ['macos-12', 'windows-2019', 'ubuntu-18.04']
-        py-version: ['3.9', '3.10', '3.11']
-        tf-version: ['2.13.0']
-        use-macos-arm: [false]
-        include:
-          - os: 'macos-12'
-            tf-version: '2.13.0'
-            py-version: '3.9'
-            use-macos-arm: true
-          - os: 'macos-12'
-            tf-version: '2.13.0'
-            py-version: '3.10'
-            use-macos-arm: true
-      fail-fast: false
-    steps:
-    - uses: actions/checkout@v2
-    - name: Set up Python
-      uses: actions/setup-python@v1
-      with:
-        python-version: ${{ matrix.py-version }}
-    - name: Get pip cache dir
-      id: pip-cache
-      run: |
-        python -m pip install --upgrade pip setuptools wheel auditwheel twine
-        echo "::set-output name=dir::$(pip cache dir)"
-    - name: pip cache
-      uses: actions/cache@v2
-      with:
-        path: ${{ steps.pip-cache.outputs.dir }}
-        key: ${{ runner.os }}-pip-${{ hashFiles('setup.py') }}
-        restore-keys: |
-          ${{ runner.os }}-pip-
-    - name: Install dependencies
-      run: |
-        python -m pip install tensorflow-cpu==${{ matrix.tf-version }}
-        python -m pip install -e ".[tests]" --progress-bar off --upgrade
-    - name: Configure Build Environment
-      run: |
-        python build_deps/configure.py
-    - name: Reinstall TensorFlow (MacOS ARM)
-      if: ${{ matrix.os == 'macos-12' && matrix.use-macos-arm}}
-      run: |
-        python -m pip uninstall -y tensorflow-cpu
-        python -m pip install --platform=macosx_12_0_arm64 --no-deps --target=$(python -c 'import site; print(site.getsitepackages()[0])') --upgrade tensorflow-macos==${{ matrix.tf-version }}
-    - name: Bazel Build
-      if: ${{ ! matrix.use-macos-arm }}
-      run: |
-        export BUILD_WITH_CUSTOM_OPS=true
-        bazel build build_pip_pkg
-    - name: Bazel Build (MacOS ARM)
-      if: ${{ matrix.use-macos-arm}}
-      run: |
-        bazel build --cpu=darwin_arm64 --copt -mmacosx-version-min=12.0 --linkopt -mmacosx-version-min=12.0 build_pip_pkg
-    - name: Build wheels
-      run: |
-        export BUILD_WITH_CUSTOM_OPS=true
-        bazel-bin/build_pip_pkg wheels
-    - name: Repair wheels (manylinux)
-      if: ${{ matrix.os == 'ubuntu-18.04' }}
-      run: |
-        python -m pip install --upgrade patchelf==0.14
-        bash build_deps/tf_auditwheel_patch.sh
-        python -m auditwheel repair --plat manylinux2014_x86_64 wheels/*.whl
-        rm wheels/*.whl
-        mv wheelhouse/* wheels/
-    - name: Upload wheels
-      env:
-        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
-        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
-      run: |
-        twine upload wheels/*
-  deploy-without-custom-ops:
-    name: Build and deploy release wheels without custom ops
+  run-test-for-release:
+    uses: ./.github/workflows/actions.yml
+  release:
+    name: Build and publish to PyPI
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
-    - name: Set up Python
-      uses: actions/setup-python@v1
-      with:
-        python-version: 3.9
-    - name: Build wheels
-      run: |
-        pip install tensorflow==2.13.0
-        python -m pip install --upgrade setuptools wheel twine
-        python -m pip install --upgrade -r requirements.txt
-        export BUILD_WITH_CUSTOM_OPS=false
-        python pip_build.py
-    - name: Upload wheels
-      env:
-        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
-        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
-      run: |
-        twine upload dist/*.whl
+      - uses: actions/checkout@v3
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.9
+      - name: Get pip cache dir
+        id: pip-cache
+        run: |
+          python -m pip install --upgrade pip setuptools
+          echo "::set-output name=dir::$(pip cache dir)"
+      - name: pip cache
+        uses: actions/cache@v2
+        with:
+          path: ${{ steps.pip-cache.outputs.dir }}
+          key: ${{ runner.os }}-pip-${{ hashFiles('setup.py') }}
+          restore-keys: |
+            ${{ runner.os }}-pip-
+      - name: Install dependencies
+        run: |
+            pip install -r requirements.txt --progress-bar off
+      - name: Build a binary wheel and a source tarball
+        run: |
+          export BUILD_WITH_CUSTOM_OPS=false
+          python pip_build.py
+      - name: Publish distribution to PyPI
+        if: startsWith(github.ref, 'refs/tags')
+        uses: pypa/gh-action-pypi-publish@master
+        with:
+          password: ${{ secrets.PYPI_API_TOKEN }}

keras_cv/backend/ops.py

@@ -16,6 +16,8 @@
 
 if keras_3():
     from keras.ops import *  # noqa: F403, F401
+    # TODO: Remove once `is_tensor` is an public API
+    from keras.src.ops import is_tensor  # noqa: F403, F401
     from keras.preprocessing.image import smart_resize  # noqa: F403, F401
 else:
     try:

keras_cv/backend/random.py

@@ -13,8 +13,63 @@
 # limitations under the License.
 
 from keras_cv.backend.config import keras_3
+from keras_cv.backend import keras
 
 if keras_3():
     from keras.random import *  # noqa: F403, F401
 else:
     from keras_core.random import *  # noqa: F403, F401
+
+
+class RandomGenerator:
+    """Random generator that selects appropriate random ops.
+
+    Created for compatibility between Keras 2 and Keras 3.
+    """
+
+    def __init__(self, seed=None, **kwargs):
+        self._seed = seed
+        self._is_keras_3 = keras_3()
+        if self._is_keras_3:
+            # Ignore args specifc to keras 2 RandomGenerator
+            kwargs.pop("force_generator", None)
+            kwargs.pop("rng_type", None)
+            self._seed_gen = keras.random.SeedGenerator(seed, **kwargs) 
+        else:
+            self._v2_random_gen = keras.backend.RadomGenerator(seed, **kwargs)
+
+    def random_normal(self, shape, mean=0.0, stddev=1.0, dtype=None):
+        """Produce random number based on the normal distribution.
+        """
+        if self._is_keras_3:
+            return keras.random.normal(shape, mean=mean, stddev=stddev, dtype=dtype, seed=self._seed_gen)
+        else:
+            return self._v2_random_gen.random_normal(shape, mean=mean, stddev=stddev, dtype=dtype)
+
+    def random_uniform(
+        self, shape, minval=0.0, maxval=None, dtype=None
+    ):
+        """Produce random number based on the uniform distribution."""
+        if self._is_keras_3:
+            return keras.random.uniform(shape, minval=minval, maxval=maxval, dtype=dtype, seed=self._seed_gen)
+        else:
+            return self._v2_random_gen.random_uniform(shape, minval=minval, maxval=maxval, dtype=dtype)
+
+
+    def truncated_normal(
+        self, shape, mean=0.0, stddev=1.0, dtype=None
+    ):
+        """Produce random number based on the truncated normal distribution."""
+        if self._is_keras_3:
+            return keras.random.truncated_normal(shape, mean=mean, stddev=stddev, dtype=dtype, seed=self._seed_gen)
+        else:
+            return self._v2_random_gen.truncated_normal(shape, mean=mean, stddev=stddev, dtype=dtype)
+
+
+    def make_legacy_seed(self):
+        """Create a new seed for the legacy stateful ops to use."""
+
+        if self._is_keras_3:
+            return self._seed_gen.next()
+        else:
+            return self._v2_random_gen.make_legacy_seed()

keras_cv/layers/preprocessing/base_image_augmentation_layer.py

@@ -25,6 +25,7 @@
 from keras_cv.backend import keras
 from keras_cv.backend import scope
 from keras_cv.backend.config import multi_backend
+from keras_cv.backend.random import RandomGenerator
 from keras_cv.utils import preprocessing
 
 # In order to support both unbatched and batched inputs, the horizontal
@@ -124,14 +125,14 @@ def augment_image(self, image, transformation):
     ```
 
     Note that since the randomness is also a common functionality, this layer
-    also includes a keras_backend.RandomGenerator, which can be used to
+    also includes RandomGenerator, which can be used to
     produce the random numbers. The random number generator is stored in the
     `self._random_generator` attribute.
     """
 
     def __init__(self, seed=None, **kwargs):
         force_generator = kwargs.pop("force_generator", False)
-        self._random_generator = keras_backend.RandomGenerator(
+        self._random_generator = RandomGenerator(
             seed=seed, force_generator=force_generator
         )
         super().__init__(**kwargs)

keras_cv/layers/preprocessing/vectorized_base_image_augmentation_layer.py

@@ -24,6 +24,7 @@
 from keras_cv.api_export import keras_cv_export
 from keras_cv.backend import keras
 from keras_cv.backend import scope
+from keras_cv.backend.random import RandomGenerator
 from keras_cv.backend.config import multi_backend
 from keras_cv.utils import preprocessing
 
@@ -103,14 +104,14 @@ def __init__(self):
     ```
 
     Note that since the randomness is also a common functionality, this layer
-    also includes a keras_backend.RandomGenerator, which can be used to
+    also includes RandomGenerator, which can be used to
     produce the random numbers. The random number generator is stored in the
     `self._random_generator` attribute.
     """
 
     def __init__(self, seed=None, **kwargs):
         force_generator = kwargs.pop("force_generator", False)
-        self._random_generator = keras_backend.RandomGenerator(
+        self._random_generator = RandomGenerator(
             seed=seed, force_generator=force_generator
         )
         super().__init__(**kwargs)

keras_cv/layers/preprocessing_3d/base_augmentation_layer_3d.py

@@ -98,7 +98,7 @@ def augment_pointclouds(self, point_clouds, transformation):
     ```
 
     Note that since the randomness is also a common functionality, this layer
-    also includes a keras.backend.RandomGenerator, which can be used to
+    also includes RandomGenerator, which can be used to
     produce the random numbers. The random number generator is stored in the
     `self._random_generator` attribute.
     """

requirements-common.txt

@@ -0,0 +1,15 @@
+# Library deps.
+absl-py
+regex
+pandas
+keras-core>=0.1.6
+tensorflow-datasets
+pycocotools
+# Tooling deps.
+packaging
+flake8
+isort
+black
+pytest
+build
+namex