import tensorflow as tf

                               lambda: ema.apply([batch_mean, batch_var]),
                               lambda: tf.no_op())

        # Update moving average and return current batch's avg and var.
        def mean_var_with_update():
            with tf.control_dependencies([ema_apply_op]):
                return tf.identity(batch_mean), tf.identity(batch_var)

        # ema.average returns the Variable holding the average of var.
        mean, var = tf.cond(is_training,
                            mean_var_with_update,
                            lambda: (ema.average(batch_mean), ema.average(batch_var)))
