Switch tensorflow_gnn/experimental/sampler/eval_dag.py to tf_internal.py

for dealing with internals of different Keras versions.

PiperOrigin-RevId: 604655724

tensorflow_gnn/experimental/sampler/eval_dag.py

@@ -27,23 +27,10 @@
 
 from tensorflow_gnn.experimental.sampler import interfaces
 from tensorflow_gnn.experimental.sampler import proto as pb
+from tensorflow_gnn.graph import tf_internal
 
-try:
-  input_layer = tf._keras_internal.engine.input_layer  # pylint:disable=g-import-not-at-top # pytype: disable=import-error # pylint:disable=protected-access
-except AttributeError:
-  try:
-    from tf_keras.src.engine import input_layer  # pylint:disable=g-import-not-at-top # pytype: disable=import-error
-  except ImportError:
-    import keras  # pylint:disable=g-import-not-at-top # pytype: disable=import-error
-    if not keras.__version__.startswith('2.'):
-      raise ImportError(
-          'tensorflow_gnn requires tf_keras to be installed or keras version <'
-          f' 3. Instead got keras version {keras.__version__}.'
-      ) from None  # This is Keras version mismatch, not just lacking tf_keras.
-    if hasattr(keras, 'src'):
-      from keras.src.engine import input_layer  # pylint:disable=g-import-not-at-top # pytype: disable=import-error
-    else:
-      from keras.engine import input_layer  # pylint:disable=g-import-not-at-top # pytype: disable=import-error
+# More portable version of input_layer = tf._keras_internal.engine.input_layer
+input_layer = tf_internal.keras_input_layer_module
 
 
 @dataclasses.dataclass

tensorflow_gnn/graph/tf_internal.py

@@ -64,6 +64,7 @@
 if tf.__version__.startswith("2.12."):
   # tf.keras is keras 2.12, which does not yet have the `src` subdirectory.
   from keras import backend as keras_backend
+  from keras.engine import input_layer
   from keras.engine import keras_tensor as kt
   from keras.layers import core as core_layers
   # In 2.12, these symbols are not exposed yet under tf.keras.__internal__.
@@ -76,30 +77,34 @@
   # tf.keras is keras.
   # For TF 2.14, there also exists a tf_keras package, but TF does not use it.
   from keras.src import backend as keras_backend
+  from keras.src.engine import input_layer
   from keras.src.engine import keras_tensor as kt
   from keras.src.layers import core as core_layers
 
 elif tf.__version__.startswith("2.15."):
   KerasTensor = tf.keras.__internal__.KerasTensor
   RaggedKerasTensor = tf.keras.__internal__.RaggedKerasTensor
-  # OSS TensorFlow 2.15 can choose between keras 2.15 and tf_keras 2.15
-  # BUT THESE ARE DIFFERENT PACKAGES WITH SEPARATE GLOBAL REGISTRIES
+  # OSS TensorFlow 2.15 can choose between keras 2.15 and tf_keras 2.15 but
+  # THESE ARE DIFFERENT PACKAGES WITH SEPARATE GLOBAL REGISTRIES (b/324019542)
   # so it is essential that we pick the right one by replicating the logic from
   # https://github.com/tensorflow/tensorflow/blob/r2.15/tensorflow/python/util/lazy_loader.py#L96
   if os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"):
     from tf_keras.src import backend as keras_backend
     from tf_keras.src.layers import core as core_layers
+    from tf_keras.src.engine import input_layer
     from tf_keras.src.engine import keras_tensor as kt
   else:
     from keras.src import backend as keras_backend
     from keras.src.layers import core as core_layers
+    from keras.src.engine import input_layer
     from keras.src.engine import keras_tensor as kt
 
 elif hasattr(tf, "_keras_internal"):  # Special case: internal.
   KerasTensor = tf.keras.__internal__.KerasTensor
   RaggedKerasTensor = tf.keras.__internal__.RaggedKerasTensor
   kt = tf._keras_internal.engine.keras_tensor  # pylint: disable=protected-access
   core_layers = tf._keras_internal.layers.core  # pylint: disable=protected-access
+  input_layer = tf._keras_internal.engine.input_layer  # pylint:disable=protected-access
   keras_backend = tf._keras_internal.backend  # pylint: disable=protected-access
 
 else:  # TF2.16 and onwards.
@@ -110,6 +115,7 @@
   RaggedKerasTensor = tf.keras.__internal__.RaggedKerasTensor
   from tf_keras.src import backend as keras_backend
   from tf_keras.src.layers import core as core_layers
+  from tf_keras.src.engine import input_layer
   from tf_keras.src.engine import keras_tensor as kt
 
 # pytype: enable=import-error
@@ -119,6 +125,9 @@
 delegate_method = core_layers._delegate_method  # pylint: disable=protected-access
 unique_keras_object_name = keras_backend.unique_object_name
 
+# tensorflow_gnn/experimental/sampler/eval_dag.py uses the module object itself.
+keras_input_layer_module = input_layer
+
 # Delete imports, in their order above.
 del composite_tensor
 del type_spec