message: Fix a dtype
diff: @@ -191,12 +191,16 @@ class _CudnnRNN(base_layer.Layer):
  invoking __call__().
  Raises:
  - ValueError: if direction is invalid.
  + ValueError: if direction is invalid. Or dtype is not supported.
  """
  super(_CudnnRNN, self).__init__(dtype=dtype, name=name)
  cudnn_rnn_ops.check_direction(direction)
  cudnn_rnn_ops.check_input_mode(input_mode)
  + if dtype not in [dtypes.float32, dtypes.float64]:
  + raise ValueError("Only support float32, float64, provided %s" % dtype)
  + # Layer self.dtype is type name, the original DType object is kept here.
  + self._plain_dtype = dtype
  self._num_layers = num_layers
  self._num_units = num_units
  self._input_mode = input_mode
  @@ -329,17 +333,17 @@ class _CudnnRNN(base_layer.Layer):
  custom_getter=self._update_trainable_weights):
  if self._kernel_initializer is None:
  self._kernel_initializer = init_ops.glorot_uniform_initializer(
  - seed=self._seed, dtype=self.dtype)
  + seed=self._seed, dtype=self._plain_dtype)
  if self._bias_initializer is None:
  self._bias_initializer = init_ops.constant_initializer(
  - 0.0, dtype=self.dtype)
  + 0.0, dtype=self._plain_dtype)
  weights = [
  - self._kernel_initializer(sp, dtype=self.dtype)
  + self._kernel_initializer(sp, dtype=self._plain_dtype)
  for sp in self.canonical_weight_shapes
  ]
  biases = [
  - self._bias_initializer(sp, dtype=self.dtype)
  + self._bias_initializer(sp, dtype=self._plain_dtype)
  for sp in self.canonical_bias_shapes
  ]
  opaque_params_t = self._canonical_to_opaque(weights, biases)
  