import tensorflow as tf

                self.y2 = tf.placeholder(tf.int32, [None, config.test_para_limit],"answer_index2")
            else:
                self.c, self.q, self.ch, self.qh, self.y1, self.y2, self.qa_id = batch.get_next()

            # self.word_unk = tf.get_variable("word_unk", shape = [config.glove_dim], initializer=initializer())
            self.word_mat = tf.get_variable("word_mat", initializer=tf.constant(
                word_mat, dtype=tf.float32), trainable=False)
            self.char_mat = tf.get_variable(
                "char_mat", initializer=tf.constant(char_mat, dtype=tf.float32))

            self.c_mask = tf.cast(self.c, tf.bool)
            self.q_mask = tf.cast(self.q, tf.bool)
            self.c_len = tf.reduce_sum(tf.cast(self.c_mask, tf.int32), axis=1)
            self.q_len = tf.reduce_sum(tf.cast(self.q_mask, tf.int32), axis=1)

            if opt:
