import tensorflow as tf

            else:
                self.embedding_W = tf.Variable(tf.random_uniform([num_quantized_chars, embedding_size], -1.0, 1.0),name="embedding_W")
            self.embedded_characters = tf.nn.embedding_lookup(self.embedding_W, self.input_x)
            embedded_text_expand = tf.expand_dims(self.embedded_characters, -1)

        with tf.device('/cpu:0'), tf.name_scope("embedding_tags"):
            W_tags = tf.get_variable("embed_W_tags", [tags_vocab_size, embedding_size], initializer=initializer)
            embedded_tags = tf.nn.embedding_lookup(W_tags, self.input_tags)
            embedded_tags_expanded = tf.expand_dims(embedded_tags, -1)

        with tf.device('/cpu:0'), tf.name_scope("embedding_deps"):
            W_deps = tf.get_variable("embed_W_deps", [deps_vocab_size, embedding_size], initializer=initializer)
            embedded_deps = tf.nn.embedding_lookup(W_deps, self.input_deps)
            embedded_deps_expanded = tf.expand_dims(embedded_deps, -1)

        with tf.device('/cpu:0'), tf.name_scope("embedding_head"):
