text: from paddle.trainer_config_helpers import *
  
  settings(learning_rate=1e-4, batch_size=1000)
  
  seq_in = data_layer(name='input', size=200)
  labels = data_layer(name='labels', size=5000)
  
  probs = data_layer(name='probs', size=10)
  xe_label = data_layer(name='xe-label', size=10)
  
  hidden = fc_layer(input=seq_in, size=4)
  outputs(
      ctc_layer(
          input=seq_in, label=labels),
      warp_ctc_layer(
          input=seq_in, label=labels, blank=0),
      crf_layer(
          input=hidden, label=data_layer(
              name='crf_label', size=4)),
      rank_cost(
          left=data_layer(
              name='left', size=1),
          right=data_layer(
              name='right', size=1),
          label=data_layer(
              name='label', size=1)),
      lambda_cost(
          input=data_layer(
              name='list_feature', size=100),
          score=data_layer(
              name='list_scores', size=1)),
      cross_entropy(
          input=probs, label=xe_label),
      cross_entropy_with_selfnorm(
          input=probs, label=xe_label),
      huber_cost(
          input=data_layer(
              name='huber_probs', size=1),
          label=data_layer(
              name='huber_label', size=1)),
      multi_binary_label_cross_entropy(
          input=probs, label=xe_label),
      sum_cost(input=hidden),
      nce_layer(
          input=hidden, label=labels))
  