def add_lr_scheduler_args(
        self,
        lr_scheduler_class: Union[LRSchedulerType, Tuple[LRSchedulerType, ...]],
        nested_key: str = "lr_scheduler",
        link_to: str = "AUTOMATIC",
    ) -> None:
        """Adds arguments from a learning rate scheduler class to a nested key of the parser.

        Args:
            lr_scheduler_class: Any subclass of ``torch.optim.lr_scheduler.{_LRScheduler, ReduceLROnPlateau}``.
            nested_key: Name of the nested namespace to store arguments.
            link_to: Dot notation of a parser key to set arguments or AUTOMATIC.

        """
        if isinstance(lr_scheduler_class, tuple):
            assert all(issubclass(o, LRSchedulerTypeTuple) for o in lr_scheduler_class)
        else:
            assert issubclass(lr_scheduler_class, LRSchedulerTypeTuple)
        kwargs = {
            "instantiate": False,
            "fail_untyped": False,
            "skip": {"optimizer"},
        }
        if isinstance(lr_scheduler_class, tuple):
            self.add_subclass_arguments(lr_scheduler_class, nested_key, required=True, **kwargs)
        else:
            self.add_class_arguments(lr_scheduler_class, nested_key, **kwargs)
        self.optimizers_and_lr_schedulers[nested_key] = (lr_scheduler_class, link_to)
Adds arguments from a learning rate scheduler class to a nested key of the parser.

        Args:
            lr_scheduler_class: Any subclass of ``torch.optim.lr_scheduler.{_LRScheduler, ReduceLROnPlateau}``.
            nested_key: Name of the nested namespace to store arguments.
            link_to: Dot notation of a parser key to set arguments or AUTOMATIC.

        
src/flash/core/utilities/lightning_cli.py