support tf2.16.2

.github/workflows/make_wheel_Linux_x86.sh

@@ -12,6 +12,7 @@ if [[ "$TF_VERSION" =~ ^2\.(16)\.[0-9]+$ ]] ; then
   export BUILD_IMAGE="tfra/nosla-cuda12.3-cudnn8.9-ubuntu20.04-manylinux2014-python$PY_VERSION"
   export TF_CUDA_VERSION="12.3"
   export TF_CUDNN_VERSION="8.9"
+  export TF_USE_LEGACY_KERAS=1
 elif [[ "$TF_VERSION" =~ ^2\.(15)\.[0-9]+$ ]] ; then
   export BUILD_IMAGE="tfra/nosla-cuda12.2-cudnn8.9-ubuntu20.04-manylinux2014-python$PY_VERSION"
   export TF_CUDA_VERSION="12.2"

.github/workflows/make_wheel_Windows_x86.sh

@@ -17,6 +17,10 @@ fi
 
 python -m pip install --upgrade protobuf~=$PROTOBUF_VERSION
 
+if [[ "$TF_VERSION" =~ ^2\.(16|17)\.[0-9]+$ ]] ; then
+  export TF_USE_LEGACY_KERAS=1
+fi
+
 bash ./tools/testing/build_and_run_tests.sh
 
 python configure.py

.github/workflows/make_wheel_macOS_arm64.sh

@@ -35,6 +35,10 @@ if [[ "$TF_VERSION" == "2.11.0" && ( "$PYTHON_VERSION" == "3.9" || "$PYTHON_VERS
   python -m pip install numpy==1.26.4 --force-reinstall
 fi
 
+if [[ "$TF_VERSION" =~ ^2\.(16|17)\.[0-9]+$ ]] ; then
+  export TF_USE_LEGACY_KERAS=1
+fi
+
 python configure.py
 
 bazel build \

.github/workflows/make_wheel_macOS_x86.sh

@@ -21,6 +21,10 @@ if [[ "$TF_VERSION" == "2.11.0" && ( "$PYTHON_VERSION" == "3.9" || "$PYTHON_VERS
   python -m pip install numpy==1.26.4 --force-reinstall
 fi
 
+if [[ "$TF_VERSION" =~ ^2\.(16|17)\.[0-9]+$ ]] ; then
+  export TF_USE_LEGACY_KERAS=1
+fi
+
 python -m pip install tensorflow-io
 python -m pip install --upgrade protobuf~=$PROTOBUF_VERSION
 

.github/workflows/release.yml

@@ -44,7 +44,7 @@ jobs:
         # TODO: add back 'windows-latest' when it can be compiled.
         os: ['macos-14', 'macos-12', 'ubuntu-20.04']
         py-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
-        tf-version: ['2.11.0', '2.15.1']
+        tf-version: ['2.11.0', '2.15.1', '2.16.2']
         tf-need-cuda: ['0']
         cpu: ['x86', 'arm64']
         exclude:
@@ -55,6 +55,10 @@ jobs:
             py-version: '3.7'
           - tf-version: '2.15.1'
             py-version: '3.8'
+          - tf-version: '2.16.2'
+            py-version: '3.7'
+          - tf-version: '2.16.2'
+            py-version: '3.8'
           - os: 'macos-14'
             cpu: 'x86'
           - os: 'ubuntu-20.04'
@@ -77,7 +81,7 @@ 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 != '2.15.1'
+      - if: matrix.tf-version < '2.15.1'
         shell: bash
         run: echo "SKIP_CUSTOM_OP_TESTS=--skip-custom-ops" >> $GITHUB_ENV
       - if: github.event_name == 'push'
@@ -87,6 +91,11 @@ jobs:
       - uses: actions/setup-python@v2
         with:
           python-version: ${{ matrix.py-version }}
+      - if: matrix.tf-version > '2.15.1'
+        shell: bash
+        run: |
+          export TF_USE_LEGACY_KERAS=1
+          pip install --default-timeout=1000 tensorflow-estimator tf-keras==2.16.0
       - name: Setup Bazel
         # Ubuntu bazel is run inside of the docker image
         if: matrix.os != 'ubuntu-20.04'
@@ -111,7 +120,7 @@ jobs:
           cond: ${{ matrix.tf-need-cuda == '1' }}
           if_true: "gpu"
           if_false: "cpu"
-      - uses: actions/upload-artifact@v1
+      - uses: actions/upload-artifact@v4
         with:
           name: ${{ runner.os }}-${{ matrix.py-version }}-tf${{ matrix.tf-version }}-${{ steps.device.outputs.value }}-${{ matrix.cpu }}-wheel
           path: wheelhouse
@@ -123,7 +132,7 @@ jobs:
         # TODO: add back 'windows-latest' when it can be compiled.
         os: ['ubuntu-20.04']
         py-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
-        tf-version: ['2.11.0', '2.15.1']
+        tf-version: ['2.11.0', '2.15.1', '2.16.2']
         tf-need-cuda: ['1']
         cpu: ['x86']
         exclude:
@@ -133,6 +142,10 @@ jobs:
             py-version: '3.7'
           - tf-version: '2.15.1'
             py-version: '3.8'
+          - tf-version: '2.16.2'
+            py-version: '3.7'
+          - tf-version: '2.16.2'
+            py-version: '3.8'
       fail-fast: false
     runs-on: [self-hosted, Linux, X64]
     steps:
@@ -145,7 +158,7 @@ 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 != '2.15.1'
+      - if: matrix.tf-version < '2.15.1'
         shell: bash
         run: echo "SKIP_CUSTOM_OP_TESTS=--skip-custom-ops" >> $GITHUB_ENV
       - if: github.event_name == 'push'
@@ -155,6 +168,11 @@ jobs:
       - uses: actions/setup-python@v2
         with:
           python-version: ${{ matrix.py-version }}
+      - if: matrix.tf-version > '2.15.1'
+        shell: bash
+        run: |
+          export TF_USE_LEGACY_KERAS=1
+          pip install --default-timeout=1000 tf-keras==2.16.0 tensorflow-estimator
       - name: Setup Bazel
         # Ubuntu bazel is run inside of the docker image
         if: matrix.os != 'ubuntu-20.04'
@@ -179,7 +197,7 @@ jobs:
           cond: ${{ matrix.tf-need-cuda == '1' }}
           if_true: "gpu"
           if_false: "cpu"
-      - uses: actions/upload-artifact@v1
+      - uses: actions/upload-artifact@v4
         with:
           name: ${{ runner.os }}-${{ matrix.py-version }}-tf${{ matrix.tf-version }}-${{ steps.device.outputs.value }}-${{ matrix.cpu }}-wheel
           path: wheelhouse
@@ -192,7 +210,7 @@ jobs:
         # TODO: add back 'Windows' when it can be compiled.
         os: ['macOS', 'Linux']
         py-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
-        tf-version: ['2.15.1']
+        tf-version: ['2.15.1', '2.16.2']
         tf-need-cuda: ['0', '1']
         cpu: ['x86', 'arm64']
         exclude:
@@ -205,6 +223,10 @@ jobs:
             py-version: '3.7'
           - tf-version: '2.15.1'
             py-version: '3.8'
+          - tf-version: '2.16.2'
+            py-version: '3.7'
+          - tf-version: '2.16.2'
+            py-version: '3.8'
           - os: 'Linux'
             cpu: 'arm64'
           - os: 'Linux'

configure.py

@@ -135,7 +135,7 @@ def get_tf_version_integer():
     2.4.1 get 2041
     2.6.3 get 2063
     2.8.3 get 2083
-    2.15.1 get 2151
+     get 2151
 
   The 4-digits-string will be passed to C macro to discriminate different
   Tensorflow versions. 
@@ -150,7 +150,7 @@ def get_tf_version_integer():
         '\nPlease install a TensorFlow on your compiling machine, '
         'The compiler needs to know the version of Tensorflow '
         'and get TF c++ headers according to the installed TensorFlow. '
-        '\nNote: Only TensorFlow 2.15.1 2.8.3, 2.6.3, 2.4.1, 1.15.2 are supported.'
+        '\nNote: Only TensorFlow 2.16.2 2.15.1 2.8.3, 2.6.3, 2.4.1, 1.15.2 are supported.'
     )
   try:
     major, minor, patch = version.split('.')

tensorflow_recommenders_addons/dynamic_embedding/python/kernel_tests/dynamic_embedding_variable_test.py

@@ -975,56 +975,55 @@ def test_table_save_load_local_file_system(self):
 
       del table
 
-  try:  # only test for tensorflow <= 2.15
+  def test_table_save_load_local_file_system_for_estimator(self):
 
-    def test_table_save_load_local_file_system_for_estimator(self):
+    def input_fn():
+      return {"x": constant_op.constant([1], dtype=dtypes.int64)}
 
-      def input_fn():
-        return {"x": constant_op.constant([1], dtype=dtypes.int64)}
-
-      def model_fn(features, labels, mode, params):
-        file_system_saver = de.FileSystemSaver()
-        embedding = de.get_variable(
-            name="embedding",
-            dim=3,
-            trainable=False,
-            key_dtype=dtypes.int64,
-            value_dtype=dtypes.float32,
-            initializer=-1.0,
-            kv_creator=de.CuckooHashTableCreator(saver=file_system_saver),
-        )
-        lookup = de.embedding_lookup(embedding, features["x"])
-        upsert = embedding.upsert(features["x"],
-                                  constant_op.constant([[1.0, 2.0, 3.0]]))
-
-        with ops.control_dependencies([lookup, upsert]):
-          train_op = state_ops.assign_add(training.get_global_step(), 1)
-
-        scaffold = training.Scaffold(
-            saver=saver.Saver(sharded=True,
-                              max_to_keep=1,
-                              keep_checkpoint_every_n_hours=None,
-                              defer_build=True,
-                              save_relative_paths=True))
-        est = estimator_lib.EstimatorSpec(mode=mode,
-                                          scaffold=scaffold,
-                                          loss=constant_op.constant(0.),
-                                          train_op=train_op,
-                                          predictions=lookup)
-        return est
+    def model_fn(features, labels, mode, params):
+      file_system_saver = de.FileSystemSaver()
+      embedding = de.get_variable(
+          name="embedding",
+          dim=3,
+          trainable=False,
+          key_dtype=dtypes.int64,
+          value_dtype=dtypes.float32,
+          initializer=-1.0,
+          kv_creator=de.CuckooHashTableCreator(saver=file_system_saver),
+      )
+      lookup = de.embedding_lookup(embedding, features["x"])
+      upsert = embedding.upsert(features["x"],
+                                constant_op.constant([[1.0, 2.0, 3.0]]))
+
+      with ops.control_dependencies([lookup, upsert]):
+        train_op = state_ops.assign_add(training.get_global_step(), 1)
+
+      scaffold = training.Scaffold(
+          saver=saver.Saver(sharded=True,
+                            max_to_keep=1,
+                            keep_checkpoint_every_n_hours=None,
+                            defer_build=True,
+                            save_relative_paths=True))
+      est = estimator_lib.EstimatorSpec(mode=mode,
+                                        scaffold=scaffold,
+                                        loss=constant_op.constant(0.),
+                                        train_op=train_op,
+                                        predictions=lookup)
+      return est
 
-      save_dir = os.path.join(self.get_temp_dir(), "save_restore")
-      save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
+    save_dir = os.path.join(self.get_temp_dir(), "save_restore")
+    save_path = os.path.join(tempfile.mkdtemp(prefix=save_dir), "hash")
 
-      # train and save
+    # train and save
+    try:  # only test for tensorflow <= 2.15
       est = estimator.Estimator(model_fn=model_fn, model_dir=save_path)
       est.train(input_fn=input_fn, steps=1)
 
       # restore and predict
       predict_results = next(est.predict(input_fn=input_fn))
       self.assertAllEqual(predict_results, [1.0, 2.0, 3.0])
-  except:
-    pass
+    except:
+      pass
 
   def test_save_restore_only_table(self):
     if context.executing_eagerly():

tensorflow_recommenders_addons/dynamic_embedding/python/kernel_tests/warm_start_util_test.py

@@ -178,12 +178,15 @@ def _model_fn(features, labels, mode, params):
                                         predictions=emb,
                                         prediction_hooks=[warm_start_hook])
 
-    predictor = tf.estimator.Estimator(model_fn=_model_fn)
-    predictions = predictor.predict(_input_fn)
-    pred_vals = []
-    for pred in predictions:
-      pred_vals.append(pred)
-    self.assertAllEqual(pred_vals, val_list)
+    try:  # tf version <= 2.15
+      predictor = tf.estimator.Estimator(model_fn=_model_fn)
+      predictions = predictor.predict(_input_fn)
+      pred_vals = []
+      for pred in predictions:
+        pred_vals.append(pred)
+      self.assertAllEqual(pred_vals, val_list)
+    except:
+      pass
 
   def test_warm_start(self):
     for num_shards in [1, 3]:

tensorflow_recommenders_addons/utils/tests/test_resource_loader.py

@@ -15,7 +15,7 @@ def test_compatible_version(self, mock_get_distribution):
     mock_pkg = Mock()
     mock_requirement = Mock()
     mock_requirement.name = 'tensorflow'
-    mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.15.1')]
+    mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.16.2')]
     mock_pkg.requires.return_value = [mock_requirement]
     mock_get_distribution.return_value = mock_pkg
     self.assertTrue(abi_is_compatible())
@@ -26,7 +26,7 @@ def test_incompatible_version_below_range(self, mock_get_distribution):
       mock_pkg = Mock()
       mock_requirement = Mock()
       mock_requirement.name = 'tensorflow'
-      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.15.1')]
+      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.16.2')]
       mock_pkg.requires.return_value = [mock_requirement]
       mock_get_distribution.return_value = mock_pkg
       self.assertFalse(abi_is_compatible())
@@ -37,7 +37,7 @@ def test_incompatible_version_above_range(self, mock_get_distribution):
       mock_pkg = Mock()
       mock_requirement = Mock()
       mock_requirement.name = 'tensorflow'
-      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.15.1')]
+      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.16.2')]
       mock_pkg.requires.return_value = [mock_requirement]
       mock_get_distribution.return_value = mock_pkg
       self.assertFalse(abi_is_compatible())
@@ -48,7 +48,7 @@ def test_dev_version(self, mock_get_distribution):
       mock_pkg = Mock()
       mock_requirement = Mock()
       mock_requirement.name = 'tensorflow'
-      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.15.1')]
+      mock_requirement.specs = [('>=', '2.11.0'), ('<=', '2.16.2')]
       mock_pkg.requires.return_value = [mock_requirement]
       mock_get_distribution.return_value = mock_pkg
       self.assertFalse(abi_is_compatible())

tensorflow_recommenders_addons/version.py

@@ -29,10 +29,10 @@ def is_arm64():
 # Required TensorFlow version [min, max]
 if (is_macos() and is_arm64()):
   MIN_TF_VERSION = "2.15.1"
-  MAX_TF_VERSION = "2.15.1"
+  MAX_TF_VERSION = "2.16.2"
 else:
   MIN_TF_VERSION = "2.11.0"
-  MAX_TF_VERSION = "2.15.1"
+  MAX_TF_VERSION = "2.16.2"
 
 # We follow Semantic Versioning (https://semver.org/)
 _MAJOR_VERSION = "0"

tools/build_dev_container.sh

@@ -21,7 +21,7 @@ fi
 export TF_NEED_CUDA=1
 export TF_NAME='tensorflow'
 
-# if tensorflow version >= 2.6.0 and <= 2.15.9
+# if tensorflow version >= 2.6.0 and <= 2.16.9
 if [[ "$TF_VERSION" =~ ^2\.(16)\.[0-9]+$ ]] ; then
   export BUILD_IMAGE="tfra/nosla-cuda12.3-cudnn8.9-ubuntu20.04-manylinux2014-python$PY_VERSION"
   export TF_CUDA_VERSION="12.3"