code: def parse_min_max_nnodes(nnodes: str):
      arr = nnodes.split(":")
  
      if len(arr) == 1:
          min_nodes = max_nodes = int(arr[0])
      elif len(arr) == 2:
          min_nodes = int(arr[0])
          max_nodes = int(arr[1])
      else:
          raise RuntimeError(
              f'nnodes={nnodes} is not in "MIN:MAX" format'
          )
  
      return min_nodes, max_nodes
  
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 3 for calling a global function with example usage: parse_min_max_nnodes(nnodes) and returns: min_nodes,  max_nodes