tensorflow 栈式双向RNN的生成

https://www.cnblogs.com/silence-tommy/p/8058333.html

tf.reverse 或 tf.reverse_sequence

具体可看tf.nn.bidirectional_dynamic_rnn()源码实现

with vs.variable_scope(scope or "bidirectional_rnn"):
  # Forward direction
  with vs.variable_scope("fw") as fw_scope:
    output_fw, output_state_fw = dynamic_rnn(
        cell=cell_fw, inputs=inputs, sequence_length=sequence_length,
        initial_state=initial_state_fw, dtype=dtype,
        parallel_iterations=parallel_iterations, swap_memory=swap_memory,
        time_major=time_major, scope=fw_scope)

def _reverse(input_, seq_lengths, seq_dim, batch_dim):
  if seq_lengths is not None:
    return array_ops.reverse_sequence(
        input=input_, seq_lengths=seq_lengths,
        seq_dim=seq_dim, batch_dim=batch_dim)
  else:
    # 大多数情况直接tf.reverse就好
    return array_ops.reverse(input_, axis=[seq_dim])

with vs.variable_scope("bw") as bw_scope:
  inputs_reverse = _reverse(
      inputs, seq_lengths=sequence_length,
      seq_dim=time_dim, batch_dim=batch_dim)
  tmp, output_state_bw = dynamic_rnn(
      cell=cell_bw, inputs=inputs_reverse, sequence_length=sequence_length,
      initial_state=initial_state_bw, dtype=dtype,
      parallel_iterations=parallel_iterations, swap_memory=swap_memory,
      time_major=time_major, scope=bw_scope)

output_bw = _reverse(
  tmp, seq_lengths=sequence_length,
  seq_dim=time_dim, batch_dim=batch_dim)

outputs = (output_fw, output_bw)
output_states = (output_state_fw, output_state_bw)

return (outputs, output_states)