code: def spawned_train(
      process_fn, opt, device_id, error_queue
  ):  # noqa: E501
      """Run `process_fn` on `device_id` with data from `batch_queue`."""
      try:
          gpu_rank = multi_init(opt, device_id)
          if gpu_rank != opt.gpu_ranks[device_id]:
              raise AssertionError(
                  "An error occurred in \
                    Distributed initialization"
              )
          process_fn(opt, device_id=device_id)
      except KeyboardInterrupt:
          pass  # killed by parent, do nothing
      except Exception:
          # propagate exception to parent process, keeping original traceback
          import traceback
  
          error_queue.put(
              (opt.gpu_ranks[device_id], traceback.format_exc())
          )
  
imports: import os
  import signal
  import math
  import pickle
  import torch.distributed
  from datetime import timedelta
  from onmt.translate.translator import build_translator
  from onmt.transforms import get_transforms_cls
  from onmt.constants import CorpusTask
  from onmt.utils.logging import init_logger, logger
  from onmt.inputters.dynamic_iterator import build_dynamic_dataset_iter
label_desc: Use image node_id 5 for calling a global function with example usage: spawned_train(process_fn, opt, device_id, error_queue) without return types