import tensorflow as tf

            raise ValueError('depth=%g is a not a valid setting!' % depth)

        # input tensors
        self.input_x = tf.placeholder(tf.int32, [None, sequence_max_length], name="input_x")
        self.input_tags = tf.placeholder(tf.int32, [None, sequence_max_length], name="input_tags")
        self.input_deps = tf.placeholder(tf.int32, [None, sequence_max_length], name="input_dependency")
        self.input_head = tf.placeholder(tf.int32, [None, sequence_max_length], name="input_head")
        self.input_y = tf.placeholder(tf.float32, [None, num_classes], name="input_y")
        self.is_training =  tf.placeholder(tf.bool)

        initializer = tf.contrib.layers.variance_scaling_initializer()

        # Embedding Lookup 16
        with tf.device('/cpu:0'), tf.name_scope("embedding"):
            if use_he_uniform:
                self.embedding_W = tf.get_variable(name='lookup_W', shape=[num_quantized_chars, embedding_size],
