import tensorflow as tf

            with tf.name_scope("UtterancesEncoder"):
                conv3 = encoder_embedding
                # conv3 = dropout(conv3, pow_1(self.dropout_keep_prob, 2))
                conv3 = conv2d_bn(
                    input=conv3,
                    filter=[1, 3, conv3.size, conv3.size * conv_mul],
                    phase_train=self.phase_train,
                    name='conv_utt_size_3_layer_1'
                )

                encoded_utterances = reduce_max(conv3, [2], keep_dims=True)

            with tf.name_scope("HistoryEncoder"):
                conv3 = encoded_utterances
                conv3 = dropout(conv3, pow_1(self.dropout_keep_prob, 2))
                conv3 = conv2d_bn(
                    input=conv3,
                    filter=[3, 1, conv3.size, conv3.size * conv_mul],
                    phase_train=self.phase_train,
                    name='conv_hist_size_3_layer_1'
                )
                conv3 = dropout(conv3, pow_1(self.dropout_keep_prob, 2))
                conv3 = conv2d_bn(
                    input=conv3,
