Add compatibility (save/restore) between CudnnGRU and CudnnCompatibleGRUCell

[danielwatson6]

Documentation has been kindly requested in the TensorFlow repo. See this issue.

[SSUHan]

Is this problem solved?
I got same problem :(
Here is my error log :

Traceback (most recent call last):
  File "evaluate.py", line 50, in <module>
    model.restore(FLAGS.model_path)
  File "/notebooks/skip-thoughts/skip_thoughts.py", line 239, in restore
    saver.restore(sess, ckpt.model_checkpoint_path)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1768, in restore
    six.reraise(exception_type, exception_value, exception_traceback)
  File "/usr/local/lib/python3.5/dist-packages/six.py", line 693, in reraise
    raise value
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1752, in restore
    {self.saver_def.filename_tensor_name: save_path})
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 900, in run
    run_metadata_ptr)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1135, in _run
    feed_dict_tensor, options, run_metadata)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1316, in _do_run
    run_metadata)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1335, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Key cudnn_gru/opaque_kernel not found in checkpoint
	 [[Node: save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save/Const_0_0, save/RestoreV2/tensor_names, save/RestoreV2/shape_and_slices)]]

Caused by op 'save/RestoreV2', defined at:
  File "evaluate.py", line 50, in <module>
    model.restore(FLAGS.model_path)
  File "/notebooks/skip-thoughts/skip_thoughts.py", line 230, in restore
    saver = tf.train.Saver(max_to_keep=1)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1284, in __init__
    self.build()
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1296, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1333, in _build
    build_save=build_save, build_restore=build_restore)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 781, in _build_internal
    restore_sequentially, reshape)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 400, in _AddRestoreOps
    restore_sequentially)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 832, in bulk_restore
    return io_ops.restore_v2(filename_tensor, names, slices, dtypes)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_io_ops.py", line 1463, in restore_v2
    shape_and_slices=shape_and_slices, dtypes=dtypes, name=name)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3414, in create_op
    op_def=op_def)
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1740, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

NotFoundError (see above for traceback): Key cudnn_gru/opaque_kernel not found in checkpoint
	 [[Node: save/RestoreV2 = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_save/Const_0_0, save/RestoreV2/tensor_names, save/RestoreV2/shape_and_slices)]]

[SSUHan]

I find how to solve this problem
change evaluation.py code like this
before :

with graph.as_default():
        model = SkipThoughts(w2v_model,
        vocabulary_size=100000, batch_size=2, output_size=512, cuda=True)

after :

with graph.as_default():
        model = SkipThoughts(w2v_model,
        vocabulary_size=20000, batch_size=2, output_size=512, cuda=True)

train.py default option for vocabulary_size is 20000 in master branch..
It's not match on evaluation.py graph