message: Add support for Eager-mode in from_keras_model_file in 1.X.
diff: @@ -50,6 +50,7 @@ from tensorflow.lite.python.util import set_tensor_shapes as _set_tensor_shapes
  from tensorflow.core.framework import graph_pb2 as _graph_pb2
  from tensorflow.python import keras as _keras
  from tensorflow.python.client import session as _session
  +from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function as _def_function
  from tensorflow.python.eager import function as _function
  from tensorflow.python.framework import convert_to_constants as _convert_to_constants
  @@ -694,6 +695,26 @@ class TFLiteConverter(object):
  Returns:
  TFLiteConverter class.
  """
  + # Handles Keras when Eager mode is enabled.
  + if context.executing_eagerly():
  + if input_arrays or input_shapes or output_arrays:
  + raise ValueError("`input_arrays`, `input_shapes` and `output_arrays`"
  + "are unsupported with Eager mode. If your model "
  + "requires any of these parameters, please use "
  + "disable_eager_execution().")
  +
  + _keras.backend.set_learning_phase(False)
  + keras_model = _keras.models.load_model(model_file, custom_objects)
  +
  + function = _saving_utils.trace_model_call(keras_model)
  + concrete_func = function.get_concrete_function()
  +
  + frozen_func = _convert_to_constants.convert_variables_to_constants_v2(
  + concrete_func)
  + return cls(frozen_func.graph.as_graph_def(), frozen_func.inputs,
  + frozen_func.outputs)
  +
  + # Handles Keras when Eager mode is disabled.
  _keras.backend.clear_session()
  _keras.backend.set_learning_phase(False)
  keras_model = _keras.models.load_model(model_file, custom_objects)
  