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: Run the chosen subcommand.
code: def _run_subcommand(self, subcommand: str) -> None:
      """Run the chosen subcommand."""
      before_fn = getattr(self, f"before_{subcommand}", None)
      if callable(before_fn):
          before_fn()
  
      default = getattr(self.trainer, subcommand)
      fn = getattr(self, subcommand, default)
      fn_kwargs = self._prepare_subcommand_kwargs(subcommand)
      fn(**fn_kwargs)
  
      after_fn = getattr(self, f"after_{subcommand}", None)
      if callable(after_fn):
          after_fn()
  
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 22 for calling the LightningCLI obj's underlying member method code with example usage: obj._run_subcommand(subcommand) without return types