[cicd]Enhance project's compatibility

Author: poinwater

.github/workflows/make_wheel_Linux_x86.sh

@@ -11,7 +11,8 @@ else
   export TF_NAME='tensorflow'
 fi
 
-if [ $TF_VERSION == "2.6.3" ]  || [ $TF_VERSION == "2.8.3" ] ; then
+# if tensorflow version >= 2.6.0 and <= 2.11.9
+if [[ "$TF_VERSION" =~ ^2\.([6-9]|10|11)\.[0-9]$ ]] ; then
   export BUILD_IMAGE="tfra/nosla-cuda11.2.1-cudnn8-ubuntu20.04-manylinux2014-python$PY_VERSION"
   export TF_CUDA_VERSION="11.2"
   export TF_CUDNN_VERSION="8.1"

.github/workflows/make_wheel_macOS_arm64.sh

@@ -2,13 +2,37 @@
 #
 # Making wheel for macOS arm64 architecture
 # Requirements: 
-# MacOS Monterey 12.0.0 +, Tensorflow-macos 2.6.0 or 2.8.0, ARM64 Apple Silicon, Bazel 4.1.0 +
+# MacOS Monterey 12.0.0 +, Tensorflow-macos 2.6.0 - 2.11.0, ARM64 Apple Silicon, Bazel 5.1.1
 # Please don't install tensorflow-metal, it may cause incorrect GPU devices detection issue.
 set -e -x
 
+export TF_NEED_CUDA=0
+if [ -z $HOROVOD_VERSION ] ; then
+  export HOROVOD_VERSION='0.28.1'
+fi
+
+# For TensorFlow version 2.12 or earlier:
+export PROTOBUF_VERSION=3.19.6
+export TF_NAME="tensorflow-macos"
+
 python --version
+python -m pip install --default-timeout=1000 delocate==0.10.3 wheel setuptools
+# For TensorFlow version 2.13 or later:
+if [[ "$TF_VERSION" =~ ^2\.1[3-9]\.[0-9]$ ]] ; then
+  export PROTOBUF_VERSION=3.20.3
+  export TF_NAME="tensorflow"
+fi
+
+python -m pip install \
+  --platform=macosx_12_0_arm64 \
+  --target=$(python -c 'import site; print(site.getsitepackages()[0])') \
+  --upgrade \
+  --only-binary=:all: \
+  protobuf~=$PROTOBUF_VERSION $TF_NAME==$TF_VERSION
 
 python configure.py
+# Setting DYLD_LIBRARY_PATH to help delocate finding tensorflow after the rpath invalidation
+export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:$(python -c 'import configure; print(configure.get_tf_shared_lib_dir())')
 
 bazel build \
   --cpu=darwin_arm64 \
@@ -20,5 +44,5 @@ bazel build \
   --test_output=errors \
   build_pip_pkg
 
-# Output the wheel file to the artifacts directory
-bazel-bin/build_pip_pkg artifacts $NIGHTLY_FLAG
+bazel-bin/build_pip_pkg artifacts "--plat-name macosx_11_0_arm64 $NIGHTLY_FLAG"
+delocate-wheel -w wheelhouse -v --ignore-missing-dependencies artifacts/*.whl

.github/workflows/make_wheel_macOS_x86.sh

@@ -2,30 +2,39 @@ set -e -x
 
 export TF_NEED_CUDA=0
 if [ -z $HOROVOD_VERSION ] ; then
-  export HOROVOD_VERSION='0.23.0'
+  export HOROVOD_VERSION='0.28.1'
 fi
 python --version
 
 brew install open-mpi
-python -m pip install numpy==1.20.0
-python -m pip install --default-timeout=1000 delocate==0.9.1 wheel==0.36.2 setuptools tensorflow==$TF_VERSION
+python -m pip install --default-timeout=1000 delocate==0.10.3 wheel==0.36.2 setuptools tensorflow==$TF_VERSION
 python -m pip install tensorflow-io
 python -m pip install --upgrade protobuf==3.20.0
 
 bash tools/docker/install/install_horovod.sh $HOROVOD_VERSION --only-cpu
 
-bash tools/testing/build_and_run_tests.sh
+# Test
+bash tools/testing/build_and_run_tests.sh $SKIP_CUSTOM_OP_TESTS
+
+# Clean
+bazel clean
+
+# Build
+python configure.py
 
 bazel build \
   -c opt \
-  --copt -mmacosx-version-min=10.13 \
-  --linkopt -mmacosx-version-min=10.13 \
+  --copt -mmacosx-version-min=10.15 \
+  --linkopt -mmacosx-version-min=10.15 \
   --noshow_progress \
   --noshow_loading_progress \
   --verbose_failures \
   --test_output=errors \
   build_pip_pkg
 
 bazel-bin/build_pip_pkg artifacts $NIGHTLY_FLAG
-delocate-wheel -w wheelhouse artifacts/*.whl
+
+# Setting DYLD_LIBRARY_PATH to help delocate finding tensorflow after the rpath invalidation
+export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:$(python -c 'import configure; print(configure.get_tf_shared_lib_dir())')
+delocate-wheel -w wheelhouse -v --ignore-missing-dependencies artifacts/*.whl
 

.github/workflows/release.yml

@@ -16,7 +16,7 @@ on:
 
 env:
   MIN_PY_VERSION: '3.7'
-  MAX_PY_VERSION: '3.9'
+  MAX_PY_VERSION: '3.10'
   HOROVOD_VERSION: '0.23.0'
 
 jobs:
@@ -25,12 +25,12 @@ jobs:
     runs-on: ubuntu-20.04
     steps:
       - uses: actions/checkout@v2
-      - uses: actions/setup-python@v1
+      - uses: actions/setup-python@v2
         with:
-          python-version: ${{ env.MIN_PY_VERSION }}
+          python-version: ${{ env.MAX_PY_VERSION }}
       - name: Build wheels
         run: |
-          pip install --default-timeout=1000 -r tools/install_deps/pytest.txt -r tools/install_deps/tensorflow-cpu.txt -r requirements.txt
+          pip install --default-timeout=1000 -r tools/install_deps/pytest.txt -r tools/install_deps/tensorflow.txt -r requirements.txt
           sudo apt install -y redis > /dev/null 2> /dev/null
           bash tools/install_deps/install_bazelisk.sh ./
           python -m pip install tensorflow-io
@@ -39,29 +39,22 @@ jobs:
           bazel test --local_ram_resources=4096 -c opt -k --test_timeout 300,450,1200,3600 --test_output=errors //tensorflow_recommenders_addons/...
   release-wheel:
     name: Build release wheels
-    runs-on: ${{ matrix.os }}
     strategy:
       matrix:
         # TODO: add back 'windows-latest' when it can be compiled.
         os: ['macos-12', 'ubuntu-20.04']
-        py-version: ['3.7', '3.8', '3.9']
-        tf-version: ['2.6.3', '2.8.3']
-        tf-need-cuda: ['1', '0']
+        py-version: ['3.7', '3.8', '3.9', '3.10']
+        tf-version: ['2.8.3', '2.11.0']
+        tf-need-cuda: ['0', '1']
         tf-cuda-version: ['11.2']
         tf-cudnn-version: ['8.1']
         cpu: ['x86']
-#       TODO(poinwater): add macOS CI once GitHub supports macOS 12.0.0 + 
-#        include:
-#          - os: 'macos-11'
-#            cpu: 'arm64'
-#            tf-version: '2.5.0'
-#            py-version: '3.9'
-#            tf-need-cuda: '0'
         exclude:
           # excludes cuda on macOS
           - os: 'macos-12'
             tf-need-cuda: '1'
       fail-fast: false
+    runs-on: ${{ matrix.os }}
     steps:
       - name: clear cache folder
         run: rm -rf /usr/share/dotnet /opt/ghc "/usr/local/share/boost"
@@ -72,11 +65,14 @@ jobs:
           script: |
             const commit_details = await github.git.getCommit({owner: context.repo.owner, repo: context.repo.repo, commit_sha: context.sha});
             return commit_details.data.author.date
+      - if: matrix.tf-version != '2.11.0'
+        shell: bash
+        run: echo "SKIP_CUSTOM_OP_TESTS=--skip-custom-ops" >> $GITHUB_ENV
       - if: github.event_name == 'push'
         shell: bash
         run: echo "NIGHTLY_FLAG=--nightly" >> $GITHUB_ENV
       - uses: actions/checkout@v2
-      - uses: actions/setup-python@v1
+      - uses: actions/setup-python@v2
         with:
           python-version: ${{ matrix.py-version }}
       - name: Setup Bazel
@@ -94,7 +90,11 @@ jobs:
           NIGHTLY_TIME: ${{ steps.author-date.outputs.result }}
           CPU: ${{ matrix.cpu }}
         shell: bash
-        run: bash .github/workflows/make_wheel_${OS}_${CPU}.sh
+        run: |
+          if [[ "$TF_VERSION" =~ ^2\.(9|10|11)\.[0-9]$ ]] ; then
+            export HOROVOD_VERSION="0.28.1"
+          fi
+          bash .github/workflows/make_wheel_${OS}_${CPU}.sh
       - uses: haya14busa/action-cond@v1
         id: device
         with:
@@ -113,17 +113,9 @@ jobs:
       matrix:
         # TODO: add back 'Windows' when it can be compiled.
         os: ['macOS', 'Linux']
-        py-version: ['3.7', '3.8', '3.9']
-        tf-version: ['2.8.3']
-        tf-need-cuda: ['1', '0']
+        py-version: ['3.7', '3.8', '3.9', '3.10']
+        tf-need-cuda: ['0', '1']
         cpu: ['x86']
-#       TODO(poinwater): add macOS CI once GitHub supports macOS 12.0.0 + 
-#        include:
-#          - os: 'macOS'
-#            cpu: 'arm64'
-#            tf-version: '2.5.0'
-#            py-version: '3.9'
-#            tf-need-cuda: '0'
         exclude:
           # excludes cuda on macOS
           - os: 'macOS'
@@ -155,7 +147,7 @@ jobs:
     runs-on: ubuntu-20.04
     strategy:
       matrix:
-        py-version: ['3.7', '3.8', '3.9']
+        py-version: ['3.7', '3.8', '3.9', '3.10']
     if: (github.event_name == 'push' && github.ref == 'refs/heads/master')
     steps:
       - uses: actions/checkout@v2

README.md

@@ -192,36 +192,26 @@ pip install artifacts/tensorflow_recommenders_addons_gpu-*.whl
 Requirements:
 
 - macOS 12.0.0+
-- Python 3.8 or 3.9
-- tensorflow-macos 2.6.0
-- bazel 4.1.0+
+- Python 3.9
+- tensorflow-macos 2.9.0
+- bazel 5.1.1
 
 The natively supported TensorFlow is maintained by Apple. Please see the instruction [Get started with tensorflow-metal](https://developer.apple.com/metal/tensorflow-plugin/) to install the Tensorflow on apple silicon devices.
 
 
-```sh
-# Install TensorFlow macOS dependencies
-conda install -c apple tensorflow-deps==2.6.0
-
-# Install base TensorFlow
-python -m pip install tensorflow-macos==2.6.0
-```
-
-If you see any issue with installing `tensorflow-macos`, please contact the [Apple Developer Forums: tensorflow-metal](https://developer.apple.com/forums/tags/tensorflow-metal) for help.
-
 **Install TFRA on Apple Silicon via PIP**
 ```sh
 python -m pip install tensorflow-recommenders-addons --no-deps
 ```
 
-**Install TFRA on Apple Silicon from Source**
+**Build TFRA on Apple Silicon from Source**
 
 ```sh
-export TF_VERSION="2.6.0"  # Specify your Tensorflow version here, 2.8.0 is well tested.
-export PY_VERSION="3.8"    # Specify your python version here, "3.9" is well tested.
+# Install bazelisk
+brew install bazelisk
 
-# Building TFRA wheel
-PY_VERSION=$PY_VERSION TF_VERSION=$TF_VERSION TF_NEED_CUDA="0" sh .github/workflows/make_wheel_macOS_arm64.sh
+# Build wheel from source
+PY_VERSION=3.9.0 TF_VERSION=2.9.0 TF_NEED_CUDA="0" sh .github/workflows/make_wheel_macOS_arm64.sh
 
 # Install the wheel
 python -m pip install --no-deps ./artifacts/*.whl

configure.py

@@ -21,23 +21,24 @@
 import logging
 
 import tensorflow as tf
+try:
+  from packaging.version import Version
+except:  # make it compatible for python 3.7
+  from distutils.version import LooseVersion as Version
 
 _TFRA_BAZELRC = ".bazelrc"
 
 
 # Maping TensorFlow version to valid Bazel version.
 def _VALID_BAZEL_VERSION(tf_version):
-  if is_macos() and is_arm64():
-    target_bazel = "4.1.0"
-    return target_bazel
-  elif tf_version < "2.0.0":
+  if Version(tf_version) < Version("2.0.0"):
     target_bazel = "0.26.1"
     logging.warn(
         'There is only limited support for TensorFlow under version 2.0.0 '
         'because its Bazel version, and requiring users to make some Bazel script changes '
         'refering to the previous COMMIT to compile properly by themselves.')
     return target_bazel
-  elif tf_version >= "2.0.0":
+  elif Version(tf_version) >= Version("2.0.0"):
     target_bazel = "5.1.1"
     logging.info(
         'To ensure code compatibility with Bazel rules_foreign_cc component, '
@@ -78,6 +79,13 @@ def is_raspi_arm():
   return os.uname()[4] == "armv7l"
 
 
+def get_cpp_version():
+  cpp_version = "c++14"
+  if Version(tf.__version__) >= Version("2.10"):
+    cpp_version = "c++17"
+  return cpp_version
+
+
 def get_tf_header_dir():
   if get_tf_version_integer() >= 2000:
     tf_header_dir = tf.sysconfig.get_compile_flags()[0][2:]
@@ -104,7 +112,10 @@ def get_tf_shared_lib_dir():
 # Converts the linkflag namespec to the full shared library name
 def get_shared_lib_name():
   namespec = tf.sysconfig.get_link_flags()
-  if is_macos():
+  if is_macos() and is_arm64():
+    # MacOS arm64
+    return "libtensorflow_framework.2.dylib"
+  elif is_macos():
     # MacOS
     return "libtensorflow_framework.dylib"
   elif is_windows():
@@ -177,14 +188,9 @@ def _get_installed_and_valid_bazel_version():
 def check_bazel_version(is_macos_arm64: bool = False):
   installed_bazel_version, valid_bazel_version = _get_installed_and_valid_bazel_version(
   )
-  if installed_bazel_version < valid_bazel_version:
-    if is_macos_arm64:
-      raise ValueError(
-          'Bazel version is {}. For macOS arm64 platform, the Bazel version must be at least {}.'
-          .format(installed_bazel_version, valid_bazel_version))
-    else:
-      raise ValueError('Bazel version is {}, but {} is needed.'.format(
-          installed_bazel_version, valid_bazel_version))
+  if Version(installed_bazel_version) < Version(valid_bazel_version):
+    raise ValueError('Bazel version is {}, but {} is needed.'.format(
+        installed_bazel_version, valid_bazel_version))
 
 
 def extract_tf_header():
@@ -227,7 +233,7 @@ def create_build_configuration():
   else:
     tf_cxx_standard_compile_flag = None
   if tf_cxx_standard_compile_flag is None:
-    tf_cxx_standard = "c++14"
+    tf_cxx_standard = get_cpp_version()
   else:
     tf_cxx_standard = tf_cxx_standard_compile_flag.split("-std=")[-1]
   write_action_env("TF_CXX_STANDARD", tf_cxx_standard)

demo/dynamic_embedding/amazon-video-games-keras-eager/main.py

@@ -3,6 +3,10 @@
 import tensorflow as tf
 
 from tensorflow_recommenders_addons import dynamic_embedding as de
+try:
+  from tensorflow.keras.optimizers.legacy import Adam
+except:
+  from tensorflow.keras.optimizers import Adam
 
 from absl import flags
 from absl import app
@@ -29,7 +33,7 @@ def train(num_steps):
   # Create a model
   model = video_game_model.VideoGameDnn(batch_size=FLAGS.batch_size,
                                         embedding_size=FLAGS.embedding_size)
-  optimizer = tf.keras.optimizers.Adam(1E-3, clipnorm=None)
+  optimizer = Adam(1E-3, clipnorm=None)
   optimizer = de.DynamicEmbeddingOptimizer(optimizer)
   auc = tf.keras.metrics.AUC(num_thresholds=1000)
   accuracy = tf.keras.metrics.BinaryAccuracy(dtype=tf.float32)

demo/dynamic_embedding/movielens-1m-keras-ps/movielens-1m-keras-ps.py

@@ -5,6 +5,10 @@
 from absl import flags
 from absl import app
 from tensorflow_recommenders_addons import dynamic_embedding as de
+try:
+  from tensorflow.keras.optimizers.legacy import Adam
+except:
+  from tensorflow.keras.optimizers import Adam
 
 flags = tf.compat.v1.app.flags
 FLAGS = flags.FLAGS
@@ -141,7 +145,7 @@ def train(self):
       model = DualChannelsDeepModel(
           self.ps_devices, self.embedding_size, self.embedding_size,
           tf.keras.initializers.RandomNormal(0.0, 0.5))
-      optimizer = tf.keras.optimizers.Adam(1E-3)
+      optimizer = Adam(1E-3)
       optimizer = de.DynamicEmbeddingOptimizer(optimizer)
 
       auc = tf.keras.metrics.AUC(num_thresholds=1000)