code: def determine_local_world_size(nproc_per_node: str):
      try:
          logging.info("Using nproc_per_node=%s.", nproc_per_node)
          return int(nproc_per_node)
      except ValueError as e:
          if nproc_per_node == "cpu":
              num_proc = os.cpu_count()
              device_type = "cpu"
          elif nproc_per_node == "gpu":
              if not torch.cuda.is_available():
                  raise ValueError("Cuda is not available.") from e
              device_type = "gpu"
              num_proc = torch.cuda.device_count()
          elif (
              nproc_per_node == torch._C._get_privateuse1_backend_name()
          ):
              if not _get_custom_mod_func("is_available")():
                  raise ValueError(
                      f"{nproc_per_node} is not available."
                  ) from e
              device_type = nproc_per_node
              num_proc = _get_custom_mod_func("device_count")()
          elif nproc_per_node == "auto":
              if torch.cuda.is_available():
                  num_proc = torch.cuda.device_count()
                  device_type = "gpu"
              elif (
                  hasattr(
                      torch, torch._C._get_privateuse1_backend_name()
                  )
                  and _get_custom_mod_func("is_available")()
              ):
                  num_proc = _get_custom_mod_func("device_count")()
                  device_type = torch._C._get_privateuse1_backend_name()
              else:
                  num_proc = os.cpu_count()
                  device_type = "cpu"
          else:
              raise ValueError(
                  f"Unsupported nproc_per_node value: {nproc_per_node}"
              ) from e
  
          log.info(
              "Using nproc_per_node=%s,"
              " setting to %s since the instance "
              "has %s %s",
              nproc_per_node,
              num_proc,
              os.cpu_count(),
              device_type,
          )
          return num_proc
  
imports: import logging
  import os
  import sys
  import uuid
  from argparse import REMAINDER, ArgumentParser
  from typing import Callable, List, Tuple, Union
  import torch
  from torch.distributed.argparse_util import check_env, env
  from torch.distributed.elastic.multiprocessing import Std
  from torch.distributed.elastic.multiprocessing.errors import record
  from torch.distributed.elastic.rendezvous.utils import _parse_rendezvous_config
  from torch.distributed.elastic.utils import macros
  from torch.distributed.elastic.utils.logging import get_logger
  from torch.distributed.launcher.api import LaunchConfig, elastic_launch
  from torch.utils.backend_registration import _get_custom_mod_func
label_desc: Use image node_id 4 for calling a global function with example usage: determine_local_world_size(nproc_per_node) and returns: int, num_proc