code: def fetch_hostfile(hostfile_path):
      if not os.path.isfile(hostfile_path):
          logger.warning(
              "Unable to find hostfile, will proceed with training "
              "with local resources only."
          )
          return None
  
      # e.g., worker-0 slots=16
      with open(hostfile_path, "r") as fd:
          resource_pool = collections.OrderedDict()
          for line in fd.readlines():
              line = line.strip()
              if line == "":
                  # skip empty lines
                  continue
              try:
                  hostname, slots = line.split()
                  _, slot_count = slots.split("=")
                  slot_count = int(slot_count)
              except ValueError as err:
                  logger.error(
                      "Hostfile is not formatted correctly, unable to "
                      "proceed with training."
                  )
                  raise err
              if hostname in resource_pool:
                  logger.error(
                      "Hostfile contains duplicate hosts, unable to "
                      "proceed with training."
                  )
                  raise ValueError(
                      f"host {hostname} is already defined"
                  )
              resource_pool[hostname] = slot_count
  
      return resource_pool
  
imports: import os
  import sys
  import json
  import base64
  import argparse
  import subprocess
  import collections
  from copy import deepcopy
  import signal
  import time
  import torch.cuda
  from .multinode_runner import PDSHRunner, OpenMPIRunner, MVAPICHRunner, SlurmRunner
  from .constants import PDSH_LAUNCHER, OPENMPI_LAUNCHER, MVAPICH_LAUNCHER, SLURM_LAUNCHER
  from ..constants import TORCH_DISTRIBUTED_DEFAULT_PORT
  from ..nebula.constants import NEBULA_EXPORT_ENVS
  from ..utils import logger
  from ..autotuning import Autotuner
label_desc: Use image node_id 2 for calling a global function with example usage: fetch_hostfile(hostfile_path) and returns: resource_pool, None