import tensorflow as tf

        with tf.variable_scope('word_char_embedding'):

            if self.config.fix_pretrained_vector:
                self.pretrained_word_mat = tf.get_variable("word_emb_mat",
                                                           [self.vocab.word_size() - 2, self.vocab.word_embed_dim],
                                                           dtype=tf.float32,
                                                           initializer=tf.constant_initializer(
                                                               self.vocab.word_embeddings[2:],
                                                               dtype=tf.float32),
                                                           trainable=False)
                self.word_pad_unk_mat = tf.get_variable("word_unk_pad",
                                                        [2, self.pretrained_word_mat.get_shape()[1]],
