def smooth_l1_loss(self, pred, label, delta=1.0 / 9.0):
        """
        Args:
            pred: pred score
            label: label
            delta: delta
        Returns: loss
        """
        assert pred.shape == label.shape and label.numel() > 0
        assert delta > 0
        diff = paddle.abs(pred - label)
        loss = paddle.where(diff < delta, 0.5 * diff * diff / delta,
                            diff - 0.5 * delta)
        return loss

        Args:
            pred: pred score
            label: label
            delta: delta
        Returns: loss
        
ppdet/modeling/heads/s2anet_head.py