About _cross_l_loss(self, hparams)

[Woooosz]

In base_model.py
def _cross_l_loss(self, hparams):
cross_l_loss = tf.zeros([1], dtype=tf.float32)
for param in self.cross_params:
cross_l_loss = tf.add(cross_l_loss, tf.multiply(hparams.cross_l1, tf.norm(param, ord=1)))
cross_l_loss = tf.add(cross_l_loss, tf.multiply(hparams.cross_l2, tf.norm(param, ord=1)))
return cross_l_loss

I wonder on Why hparams.cross_l2 doesn't multiply with tf.norm(param, ord=2)?