seq2seq.py 文件源码

def variational_encoder_with_buckets(encoder_inputs, buckets, encoder,
                       enc_latent, softmax_loss_function=None,
                       per_example_loss=False, name=None):
  """Create a sequence-to-sequence model with support for bucketing.
  """
  if len(encoder_inputs) < buckets[-1][0]:
    raise ValueError("Length of encoder_inputs (%d) must be at least that of la"
                     "st bucket (%d)." % (len(encoder_inputs), buckets[-1][0]))

  all_inputs = encoder_inputs
  means = []
  logvars = []
  with ops.name_scope(name, "variational_encoder_with_buckets", all_inputs):
    for j, bucket in enumerate(buckets):
      with variable_scope.variable_scope(variable_scope.get_variable_scope(),
                                         reuse=True if j > 0 else None):
        encoder_last_state = encoder(encoder_inputs[:bucket[0]])
        mean, logvar = enc_latent(encoder_last_state)
        means.append(mean)
        logvars.append(logvar)

  return means, logvars