import tensorflow as tf

                    initializer=tf.constant_initializer(self.vocab.char_embeddings),
                    trainable=True
                )

            self.ch_len = tf.reshape(tf.reduce_sum(
                tf.cast(tf.cast(self.ch, tf.bool), tf.int32), axis=2), [-1])
            self.qh_len = tf.reshape(tf.reduce_sum(
                tf.cast(tf.cast(self.qh, tf.bool), tf.int32), axis=2), [-1])

        N, PL, QL, CL, d, dc, nh = self._params()

        if self.config.fix_pretrained_vector:
            dc = self.char_mat.get_shape()[-1]
        with tf.variable_scope("Input_Embedding_Layer"):
