ce11b92597b32bccf9999e94550855e55e02da9b,sonnet/python/modules/basic_rnn.py,DeepRNN,_build,#DeepRNN#Any#Any#,312

Before Change

    for i, core in enumerate(self._cores):
      if self._skip_connections and i > 0:
        flat_input = (nest.flatten(inputs), nest.flatten(current_input))
        flat_input = [tf.concat(input_, 1) for input_ in zip(*flat_input)]
        current_input = nest.pack_sequence_as(structure=inputs,
                                              flat_sequence=flat_input)

After Change

        outputs.append(current_input)

    if self._skip_connections and self._concat_final_output_if_skip:
      output = nest.map_structure(concatenate, *outputs)
    else:
      output = current_input

    self._last_output_size = _get_shape_without_batch_dimension(output)

Instances