import tensorflow as tf

                length=histories_vocabulary_length,
                size=histories_embedding_size,
                name='encoder_embedding'
            )

            with tf.name_scope("UtterancesEncoder"):
                conv3 = encoder_embedding
                # conv3 = dropout(conv3, pow_1(self.dropout_keep_prob, 2))
                conv3 = conv2d_bn(
                    input=conv3,
