class_docstr: Implementation of a configurable command line tool for pytorch-lightning.
class_docstr_tok: ["Implementation","of","a","configurable","command","line","tool","for","pytorch-lightning","."]
docstr: Adds subcommands to the input parser.
code: def _add_subcommands(
      self, parser: LightningArgumentParser, **kwargs: Any
  ) -> None:
      """Adds subcommands to the input parser."""
      self._subcommand_parsers: Dict[str, LightningArgumentParser] = {}
      parser_subcommands = parser.add_subcommands()
      # the user might have passed a builder function
      trainer_class = (
          self.trainer_class
          if isinstance(self.trainer_class, type)
          else class_from_function(self.trainer_class)
      )
      # register all subcommands in separate subcommand parsers under the main parser
      for subcommand in self.subcommands():
          fn = getattr(trainer_class, subcommand)
          # extract the first line description in the docstring for the subcommand help message
          description = _get_short_description(fn)
          subparser_kwargs = kwargs.get(subcommand, {})
          subparser_kwargs.setdefault("description", description)
          subcommand_parser = self._prepare_subcommand_parser(
              trainer_class, subcommand, **subparser_kwargs
          )
          self._subcommand_parsers[subcommand] = subcommand_parser
          parser_subcommands.add_subcommand(
              subcommand, subcommand_parser, help=description
          )
  
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 10 for calling the LightningCLI obj's underlying member method code with example usage: obj._add_subcommands(parser) without return types