Understanding the GIoU loss function in tensorflow

The custom Loss function I am looking at is as follows:

@tf.keras.utils.register_keras_serializable(package="Addons")
    class GIoULoss(LossFunctionWrapper):
@typechecked
    def __init__(
        self,
        mode: str = "giou",
        reduction: str = tf.keras.losses.Reduction.AUTO,
        name: Optional[str] = "giou_loss",
    ):
        super().__init__(giou_loss, name=name, reduction=reduction, mode=mode)

@tf.keras.utils.register_keras_serializable(package="Addons")
def giou_loss(y_true: TensorLike, y_pred: TensorLike, mode: str = "giou") -> tf.Tensor:

My questions:

1. Majority of the custom loss functions I have looked at work without using LossFunctionWrapper. So under what circumstances is LossFunctionWrapper used and when can you work without it?
2. I haven't been able to fully understand from the tensorflow documentation what @tf.keras.utils.register_keras_serializable(package="Addons") does. Any help?