import tensorflow as tf

      embedding_output = modeling.embedding_postprocessor(
          input_tensor=word_embedding_output,
          use_token_type=True,
          token_type_ids=segment_ids,
          token_type_vocab_size=config.type_vocab_size,
          token_type_embedding_name="token_type_embeddings",
          use_position_embeddings=True,
          position_embedding_name="position_embeddings",
          initializer_range=config.initializer_range,
          max_position_embeddings=config.max_position_embeddings,
          dropout_prob=config.hidden_dropout_prob)
  with tf.variable_scope("bilstm"):
    sequence_output = modeling.bilstm_fused(
      inputs=embedding_output, 
      sequence_lengths=_true_length, 
      lstm_size=config.lstm_size,
      bilstm_dropout_rate=config.bilstm_dropout_rate, 
      is_training=is_training,
      num_layers=config.num_bilstm)
  # with tf.variable_scope("bilstm"):
  #   sequence_output, _ = modeling.cudnn_rnn(
  #     inputs=embedding_output, 
