code: def distributed_main(device_id, configuration, predict=False):
      config = configuration.get_config()
      config.device_id = device_id
  
      if config.distributed.rank is None:
          config.distributed.rank = config.start_rank + device_id
  
      main(configuration, init_distributed=True, predict=predict)
  
file_path: mmf/mmf_cli/run.py
imports: import argparse
  import logging
  import random
  import typing
  import torch
  from mmf.common.registry import registry
  from mmf.utils.build import build_config, build_trainer
  from mmf.utils.configuration import Configuration
  from mmf.utils.distributed import distributed_init, get_rank, infer_init_method, is_xla
  from mmf.utils.env import set_seed, setup_imports
  from mmf.utils.flags import flags
  from mmf.utils.general import log_device_names
  from mmf.utils.logger import setup_logger, setup_very_basic_config
label_desc: Use image node_id 2 for calling a global function with example usage: distributed_main(device_id, configuration, predict) without return types