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: Sets the seed.
code: def _set_seed(self) -> None:
      """Sets the seed."""
      config_seed = self._get(self.config, "seed_everything")
      if config_seed is False:
          return
      if config_seed is True:
          # user requested seeding, choose randomly
          config_seed = seed_everything(workers=True)
      else:
          config_seed = seed_everything(config_seed, workers=True)
      if self.subcommand:
          self.config[self.subcommand]["seed_everything"] = config_seed
      else:
          self.config["seed_everything"] = config_seed
  
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 24 for calling the LightningCLI obj's underlying member method code with example usage: obj._set_seed() without return types