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: Prepares the keyword arguments to pass to the subcommand to run.
code: def _prepare_subcommand_kwargs(
      self, subcommand: str
  ) -> Dict[str, Any]:
      """Prepares the keyword arguments to pass to the subcommand to run."""
      fn_kwargs = {
          k: v
          for k, v in self.config_init[subcommand].items()
          if k in self._subcommand_method_arguments[subcommand]
      }
      fn_kwargs["model"] = self.model
      if self.datamodule is not None:
          fn_kwargs["datamodule"] = self.datamodule
      return fn_kwargs
  
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 23 for calling the LightningCLI obj's underlying member method code with example usage: obj._prepare_subcommand_kwargs(subcommand) and returns: fn_kwargs