code: def _suggested_max_num_threads(num_processes: int = 1) -> int:
      if num_processes < 1:
          raise ValueError(
              f"`num_processes` should be >= 1, got {num_processes}."
          )
      return max(1, _num_cpus_available() // num_processes)
  
imports: import contextlib
  import logging
  import os
  import time
  from contextlib import nullcontext
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Iterable, Iterator, List, Optional, Sized, Union
  import torch
  import torch.nn.functional
  from lightning_utilities.core.imports import package_available
  from torch import Tensor
  from torch.utils.data import Dataset, DistributedSampler, Sampler
  from typing_extensions import override
  from lightning.fabric.utilities.cloud_io import _is_local_file_protocol
  from lightning.fabric.utilities.data import _num_cpus_available
  from lightning.fabric.utilities.rank_zero import rank_zero_info
  from lightning.fabric.utilities.types import _PATH, ReduceOp
label_desc: Use image node_id 9 for calling a global function with example usage: _suggested_max_num_threads(num_processes) and returns: max