import tensorflow as tf

            batch_mean, batch_var = tf.nn.moments(x, range(len(shape) - 1))
            update_mean = tf.assign_sub(pop_mean, (1 - decay)*(pop_mean - batch_mean))
            update_var = tf.assign_sub(pop_var, (1 - decay)*(pop_var - batch_var))
            with tf.control_dependencies([update_mean, update_var]):
                return tf.nn.batch_normalization(x, batch_mean, batch_var, beta, gamma, epsilon)

        def func2():
            # execute at test time
