class_docstr: Extension of jsonargparse's ArgumentParser for pytorch-lightning.
class_docstr_tok: ["Extension","of","jsonargparse","'s","ArgumentParser","for","pytorch-lightning","."]
docstr: 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}``. Use
          tuple to allow subclasses.
      nested_key: Name of the nested namespace to store arguments.
      link_to: Dot notation of a parser key to set arguments or AUTOMATIC.
code: def add_lr_scheduler_args(
      self,
      lr_scheduler_class: Union[
          LRSchedulerType, Tuple[LRSchedulerType, ...]
      ] = LRSchedulerTypeTuple,
      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}``. Use
              tuple to allow subclasses.
          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: Dict[str, Any] = {
          "instantiate": False,
          "fail_untyped": False,
          "skip": {"optimizer"},
      }
      if isinstance(lr_scheduler_class, tuple):
          self.add_subclass_arguments(
              lr_scheduler_class, nested_key, **kwargs
          )
      else:
          self.add_class_arguments(
              lr_scheduler_class, nested_key, sub_configs=True, **kwargs
          )
      self._lr_schedulers[nested_key] = (lr_scheduler_class, link_to)
  
imports: import os
  import sys
  from functools import partial, update_wrapper
  from types import MethodType
  from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Type, Union
  import torch
  from lightning_utilities.core.imports import RequirementCache
  from lightning_utilities.core.rank_zero import _warn
  from torch.optim import Optimizer
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.utilities.cloud_io import get_filesystem
  from lightning.fabric.utilities.types import _TORCH_LRSCHEDULER
  from lightning.pytorch import Callback, LightningDataModule, LightningModule, Trainer, seed_everything
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.model_helpers import is_overridden
  from lightning.pytorch.utilities.rank_zero import rank_zero_warn
label_desc: Use image node_id 4 for calling the LightningArgumentParser obj's underlying member method code with example usage: obj.add_lr_scheduler_args(lr_scheduler_class, nested_key, link_to) without return types