Refactor keras dependency code

PiperOrigin-RevId: 339954904
Change-Id: Id9f6717da5c32bff185a10a37e9682be64cc6501

tensorflow/lite/python/BUILD

@@ -149,7 +149,6 @@ py_library(
         "//tensorflow/lite/experimental/examples/lstm:tflite_lstm_ops",
         "//tensorflow/lite/experimental/microfrontend:audio_microfrontend_py",
         "//tensorflow/lite/experimental/tensorboard:ops_util",
-        "//tensorflow/lite/python/keras/saving:saving_utils",
         "//tensorflow/lite/python/optimize:calibrator",
         "//tensorflow/python:graph_util",
         "//tensorflow/python/keras",
@@ -236,6 +235,7 @@ py_library(
         ":op_hint",
         ":schema_py",
         ":schema_util",
+        "//tensorflow/lite/python:tflite_keras_util",
         "//tensorflow/lite/toco:toco_flags_proto_py",
         "//tensorflow/python:convert_to_constants",
         "//tensorflow/python:dtypes",
@@ -278,6 +278,18 @@ py_test(
     ],
 )
 
+py_library(
+    name = "tflite_keras_util",
+    srcs = [
+        "tflite_keras_util.py",
+    ],
+    srcs_version = "PY2AND3",
+    deps = [
+        "//tensorflow/python:util",
+        "//tensorflow/python/eager:def_function",
+    ],
+)
+
 py_library(
     name = "wrap_toco",
     srcs = [

tensorflow/lite/python/keras/saving/BUILD

-package(
-    default_visibility = ["//visibility:public"],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-py_library(
-    name = "saving_utils",
-    srcs = [
-        "saving_utils.py",
-    ],
-    srcs_version = "PY2AND3",
-    deps = [
-        "//tensorflow/python:util",
-        "//tensorflow/python/eager:def_function",
-    ],
-)

tensorflow/lite/python/lite.py

@@ -50,7 +50,6 @@ from tensorflow.lite.python.convert import toco_convert_protos  # pylint: disabl
 from tensorflow.lite.python.convert_saved_model import freeze_saved_model as _freeze_saved_model
 from tensorflow.lite.python.interpreter import Interpreter  # pylint: disable=unused-import
 from tensorflow.lite.python.interpreter import load_delegate  # pylint: disable=unused-import
-from tensorflow.lite.python.keras.saving import saving_utils as _keras_saving_utils
 from tensorflow.lite.python.op_hint import convert_op_hints_to_stubs  # pylint: disable=unused-import
 from tensorflow.lite.python.op_hint import is_ophint_converted as _is_ophint_converted
 from tensorflow.lite.python.op_hint import OpHint  # pylint: disable=unused-import
@@ -63,9 +62,11 @@ from tensorflow.lite.python.util import get_grappler_config as _get_grappler_con
 from tensorflow.lite.python.util import get_tensor_name as _get_tensor_name
 from tensorflow.lite.python.util import get_tensors_from_tensor_names as _get_tensors_from_tensor_names
 from tensorflow.lite.python.util import is_frozen_graph as _is_frozen_graph
+from tensorflow.lite.python.util import model_input_signature as _model_input_signature
 from tensorflow.lite.python.util import modify_model_io_type as _modify_model_io_type
 from tensorflow.lite.python.util import run_graph_optimizations as _run_graph_optimizations
 from tensorflow.lite.python.util import set_tensor_shapes as _set_tensor_shapes
+from tensorflow.lite.python.util import trace_model_call as _trace_model_call
 from tensorflow.python.client import session as _session
 from tensorflow.python.eager import context
 from tensorflow.python.eager import def_function as _def_function
@@ -839,12 +840,11 @@ class TFLiteKerasModelConverterV2(TFLiteConverterBaseV2):
       # Pass `keep_original_batch_size=True` will ensure that we get an input
       # signature including the batch dimension specified by the user.
       # TODO(b/169898786): Use the Keras public API when TFLite moves out of TF
-      input_signature = _keras_saving_utils.model_input_signature(
+      input_signature = _model_input_signature(
           self._keras_model, keep_original_batch_size=True)
 
     # TODO(b/169898786): Use the Keras public API when TFLite moves out of TF
-    func = _keras_saving_utils.trace_model_call(
-        self._keras_model, input_signature)
+    func = _trace_model_call(self._keras_model, input_signature)
     concrete_func = func.get_concrete_function()
     self._funcs = [concrete_func]
 
@@ -1468,7 +1468,7 @@ class TFLiteKerasModelConverter(TFLiteConverterBaseV1):
 
       keras_model = keras_deps.get_load_model_function()(
           model_file, custom_objects)
-      function = _keras_saving_utils.trace_model_call(keras_model)
+      function = _trace_model_call(keras_model)
       concrete_func = function.get_concrete_function()
 
       frozen_func = _convert_to_constants.convert_variables_to_constants_v2(

tensorflow/lite/python/keras/saving/saving_utils.py → tensorflow/lite/python/tflite_keras_util.py

@@ -13,7 +13,13 @@
 # limitations under the License.
 # ==============================================================================
 
-"""Utility functions for TensorFlow models."""
+"""Keras functions required by TensorFlow Lite.
+
+The functions defined in this library have been copied over from Keras in order
+to remove the dependency from TensorFlow Lite to Keras. The functions which
+could not be copied over are accessed using the dependecy inversion principle.
+(for details, refer to tensorflow/python/util/keras_deps.py).
+"""
 
 from __future__ import absolute_import
 from __future__ import division

tensorflow/lite/python/util.py

@@ -33,6 +33,7 @@ from tensorflow.core.protobuf import graph_debug_info_pb2
 from tensorflow.core.protobuf import meta_graph_pb2 as _meta_graph_pb2
 from tensorflow.lite.python import schema_py_generated as schema_fb
 from tensorflow.lite.python import schema_util
+from tensorflow.lite.python import tflite_keras_util as _tflite_keras_util
 from tensorflow.lite.python.op_hint import convert_op_hints_to_stubs
 from tensorflow.lite.python.op_hint import find_all_hinted_output_nodes
 from tensorflow.lite.toco import types_pb2 as _types_pb2
@@ -44,6 +45,10 @@ from tensorflow.python.framework import graph_util as tf_graph_util
 from tensorflow.python.grappler import tf_optimizer
 from tensorflow.python.training.saver import export_meta_graph as _export_meta_graph
 
+# Keras functions used by TFLite
+model_input_signature = _tflite_keras_util.model_input_signature
+trace_model_call = _tflite_keras_util.trace_model_call
+
 # Map of tf.dtypes to TFLite types_flag_pb2.
 _MAP_TF_TO_TFLITE_TYPES = {
     dtypes.float32: _types_pb2.FLOAT,

tensorflow/python/keras/engine/base_layer_utils.py

@@ -417,6 +417,8 @@ def call_context():
   return call_ctx
 
 
+# Inject the call_context function to keras_deps to remove the dependency
+# from TFLite to Keras.
 keras_deps.register_call_context_function(call_context)