code: def set_torch_seed(seed: Optional[int] = None) -> None:
      """Sets the torch random seed to the given value.
  
      Args:
          seed: The seed to use or None for no seeding.
      """
      if seed is not None and torch:
          torch.manual_seed(seed)
          # See https://github.com/pytorch/pytorch/issues/47672.
          cuda_version = torch.version.cuda
          if (
              cuda_version is not None
              and float(torch.version.cuda) >= 10.2
          ):
              os.environ["CUBLAS_WORKSPACE_CONFIG"] = "4096:8"
          else:
              # Not all Operations support this.
              torch.use_deterministic_algorithms(True)
          # This is only for Convolution no problem.
          torch.backends.cudnn.deterministic = True
  
imports: import logging
  import os
  import warnings
  from typing import Dict, List, Optional, TYPE_CHECKING, Union
  import gymnasium
  import numpy
  import tree
  from gymnasium.spaces import Discrete, MultiDiscrete
  from packaging import version
  import ray
  from ray.rllib.models.repeated_values import RepeatedValues
  from ray.rllib.utils.annotations import Deprecated, PublicAPI, DeveloperAPI
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.numpy import SMALL_NUMBER
  from ray.rllib.utils.typing import LocalOptimizer, SpaceStruct, TensorStructType, TensorType
label_desc: Use image node_id 19 for calling a global function with example usage: set_torch_seed(seed) without return types