import tensorflow as tf

            init_scale = .01
            m_init, v_init = tf.nn.moments(x, [0, 1, 2])
            scale_init = init_scale / tf.sqrt(v_init + 1e-10)
            with tf.control_dependencies([g.assign(g * scale_init), b.assign_add(-m_init * scale_init)]):
                x = tf.reshape(scale_init, [1, 1, 1, num_filters]) * (x - tf.reshape(m_init, [1, 1, 1, num_filters]))

        else:
            V = maybe_avg(V)
