import tensorflow as tf

          sequence_length=text_len,
          initial_state_fw=state_fw,
          initial_state_bw=state_bw)

        text_outputs = tf.concat([fw_outputs, bw_outputs], 2) # [num_sentences, max_sentence_length, emb]
        text_outputs = tf.nn.dropout(text_outputs, self.lstm_dropout)
        if layer > 0:
          highway_gates = tf.sigmoid(util.projection(text_outputs, util.shape(text_outputs, 2))) # [num_sentences, max_sentence_length, emb]
          text_outputs = highway_gates * text_outputs + (1 - highway_gates) * current_inputs
        current_inputs = text_outputs
