code: def spawn_main(main, args):
      if args.distributed:
          torch.multiprocessing.spawn(
              main, args=(args,), nprocs=args.world_size, join=True
          )
      else:
          main(0, args)
  
imports: import argparse
  import logging
  import os
  import string
  from datetime import datetime
  from time import time
  import torch
  import torchaudio
  from ctc_decoders import GreedyDecoder
  from datasets import collate_factory, split_process_librispeech
  from languagemodels import LanguageModel
  from torch.optim import Adadelta, Adam, AdamW, SGD
  from torch.optim.lr_scheduler import ExponentialLR, ReduceLROnPlateau
  from torch.utils.data import DataLoader
  from torchaudio.functional import edit_distance
  from torchaudio.models.wav2letter import Wav2Letter
  from transforms import Normalize, UnsqueezeFirst
  from utils import count_parameters, MetricLogger, save_checkpoint
label_desc: Use image node_id 8 for calling a global function with example usage: spawn_main(main, args) without return types