message: forward compat
diff: @@ -20,6 +20,7 @@ from __future__ import print_function
  import os
  from tensorflow.contrib.checkpoint.python import split_dependency
  from tensorflow.contrib.rnn.python.ops import lstm_ops
  +from tensorflow.python.compat import compat
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  @@ -249,6 +250,7 @@ class CudnnParamsFormatConverter(object):
  2 list for weights and biases respectively.
  """
  with ops.device("/gpu:0"):
  + if compat.forward_compatible(2019, 6, 26):
  if self._num_proj:
  num_params_weights = (self._num_params +
  1 * self._num_layers * self._num_dirs)
  @@ -276,6 +278,17 @@ class CudnnParamsFormatConverter(object):
  direction=self._direction)
  return (weights, biases)
  + weights, biases = gen_cudnn_rnn_ops.cudnn_rnn_params_to_canonical(
  + num_layers=self._num_layers,
  + num_units=self._num_units,
  + input_size=self._input_size,
  + params=opaque_param,
  + num_params=self._num_params,
  + rnn_mode=self._rnn_mode,
  + input_mode=self._input_mode,
  + direction=self._direction)
  + return (weights, biases)
  +
  def _cu_canonical_to_opaque(self, cu_weights, cu_biases):
  """Converts from Cudnn canonical format to opaque params.
  @@ -287,6 +300,7 @@ class CudnnParamsFormatConverter(object):
  a single opaque tensor.
  """
  with ops.device("/gpu:0"):
  + if compat.forward_compatible(2019, 6, 26):
  if self._num_proj:
  return gen_cudnn_rnn_ops.cudnn_rnn_canonical_to_params_v2(
  num_layers=self._num_layers,
  @@ -309,6 +323,16 @@ class CudnnParamsFormatConverter(object):
  input_mode=self._input_mode,
  direction=self._direction)
  + return gen_cudnn_rnn_ops.cudnn_rnn_canonical_to_params(
  + num_layers=self._num_layers,
  + num_units=self._num_units,
  + input_size=self._input_size,
  + weights=cu_weights,
  + biases=cu_biases,
  + rnn_mode=self._rnn_mode,
  + input_mode=self._input_mode,
  + direction=self._direction)
  +
  def _cu_canonical_to_tf_canonical(self, cu_weights, cu_biases):
  r"""Transform from Cudnn canonical to tf canonical.
  