L2 weight decay loss.

def _decay(self):
        """L2 weight decay loss."""
        costs = []
        for var in tf.trainable_variables():
            if var.op.name.find(r"DW") > 0:
                costs.append(tf.nn.l2_loss(var))

        return tf.multiply(self.hps.weight_decay_rate, tf.add_n(costs))