message: try to remove keras deps
diff: @@ -23,8 +23,6 @@ from __future__ import print_function
  import itertools
  from tensorflow.lite.python.op_hint import OpHint
  -from tensorflow.python.keras import activations
  -from tensorflow.python.keras import initializers
  from tensorflow.python.layers import base as base_layer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import clip_ops
  @@ -80,7 +78,9 @@ class TfLiteRNNCell(rnn_cell_impl.LayerRNNCell):
  self._tflite_wrapper = OpHint("UnidirectionalSequenceRnn")
  self._num_units = num_units
  if activation:
  - self._activation = activations.get(activation)
  + if activation != "tanh":
  + raise ValueError("activation other than tanh is not supported")
  + self._activation = math_ops.tanh
  else:
  self._activation = math_ops.tanh
  @@ -150,7 +150,7 @@ class TfLiteRNNCell(rnn_cell_impl.LayerRNNCell):
  def get_config(self):
  config = {
  "num_units": self._num_units,
  - "activation": activations.serialize(self._activation),
  + "activation": "tanh",
  "reuse": self._reuse,
  }
  base_config = super(TfLiteRNNCell, self).get_config()
  @@ -268,7 +268,12 @@ class TFLiteLSTMCell(rnn_cell_impl.LayerRNNCell):
  self._num_proj_shards = num_proj_shards
  self._forget_bias = forget_bias
  self._state_is_tuple = state_is_tuple
  - self._activation = activation or math_ops.tanh
  + if activation:
  + if activation != "tanh":
  + raise ValueError("activation other than tanh is not supported")
  + self._activation = math_ops.tanh
  + else:
  + self._activation = math_ops.tanh
  self._output_size = num_proj if num_proj else num_units
  self._state_size = (
  @@ -516,14 +521,13 @@ class TFLiteLSTMCell(rnn_cell_impl.LayerRNNCell):
  "num_units": self._num_units,
  "use_peepholes": self._use_peepholes,
  "cell_clip": self._cell_clip,
  - "initializer": initializers.serialize(self._initializer),
  "num_proj": self._num_proj,
  "proj_clip": self._proj_clip,
  "num_unit_shards": self._num_unit_shards,
  "num_proj_shards": self._num_proj_shards,
  "forget_bias": self._forget_bias,
  "state_is_tuple": self._state_is_tuple,
  - "activation": activations.serialize(self._activation),
  + "activation": "tanh",
  "reuse": self._reuse,
  }
  base_config = super(TFLiteLSTMCell, self).get_config()
  