import tensorflow as tf

        dec = tf.layers.max_pooling1d(dec, pool_size=2, strides=1, padding="same")
        dec = tf.layers.conv1d(dec, embed_size // 2, 3, name="decoder-conv1-1", padding="SAME")
        dec = tf.nn.relu(tf.layers.batch_normalization(dec, training=self.training))
        dec = tf.layers.conv1d(dec, embed_size // 2, 3, name="decoder-conv1-2", padding="SAME")
        dec = tf.layers.batch_normalization(dec, training=self.training)
        dec = tf.layers.dense(dec, embed_size // 2)
        for i in range(4):
            dec = highwaynet(
                dec, num_units=embed_size // 2, scope="decoder-highwaynet-{}".format(i)
            )
