code: def _set_torch_flags(
      *,
      deterministic: Optional[Union[bool, _LITERAL_WARN]] = None,
      benchmark: Optional[bool] = None,
  ) -> None:
      if deterministic:
          if benchmark is None:
              # Set benchmark to False to ensure determinism
              benchmark = False
          elif benchmark:
              rank_zero_warn(
                  "You passed `deterministic=True` and `benchmark=True`. Note that PyTorch ignores"
                  " torch.backends.cudnn.deterministic=True when torch.backends.cudnn.benchmark=True.",
              )
      if benchmark is not None:
          torch.backends.cudnn.benchmark = benchmark
  
      if deterministic == "warn":
          torch.use_deterministic_algorithms(True, warn_only=True)
      elif isinstance(deterministic, bool):
          # do not call this if deterministic wasn't passed
          torch.use_deterministic_algorithms(deterministic)
      if deterministic:
          # https://docs.nvidia.com/cuda/cublas/index.html#cublasApi_reproducibility
          os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"
  
imports: import logging
  import os
  from collections import Counter
  from typing import Dict, List, Literal, Optional, Union
  import torch
  from lightning.fabric.connector import _PRECISION_INPUT, _PRECISION_INPUT_STR, _convert_precision_to_unified_args
  from lightning.fabric.plugins.environments import ClusterEnvironment, LightningEnvironment, LSFEnvironment, MPIEnvironment, SLURMEnvironment, TorchElasticEnvironment
  from lightning.fabric.utilities.device_parser import _determine_root_gpu_device
  from lightning.fabric.utilities.imports import _IS_INTERACTIVE
  from lightning.pytorch.accelerators import AcceleratorRegistry
  from lightning.pytorch.accelerators.accelerator import Accelerator
  from lightning.pytorch.accelerators.cuda import CUDAAccelerator
  from lightning.pytorch.accelerators.mps import MPSAccelerator
  from lightning.pytorch.accelerators.xla import XLAAccelerator
  from lightning.pytorch.plugins import _PLUGIN_INPUT, CheckpointIO, DeepSpeedPrecision, DoublePrecision, FSDPPrecision, HalfPrecision, MixedPrecision, Precision, TransformerEnginePrecision, XLAPrecision
  from lightning.pytorch.plugins.layer_sync import LayerSync, TorchSyncBatchNorm
  from lightning.pytorch.strategies import DDPStrategy, DeepSpeedStrategy, FSDPStrategy, ParallelStrategy, SingleDeviceStrategy, SingleDeviceXLAStrategy, Strategy, StrategyRegistry, XLAStrategy
  from lightning.pytorch.strategies.ddp import _DDP_FORK_ALIASES
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.imports import _LIGHTNING_BAGUA_AVAILABLE, _LIGHTNING_COLOSSALAI_AVAILABLE, _graphcore_available_and_importable, _habana_available_and_importable
  from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn
label_desc: Use image node_id 1 for calling a global function with example usage: _set_torch_flags() without return types