code: def bmuf_process(self, cfg, args, iterations):
      results = Manager().dict()
      torch.multiprocessing.spawn(
          fn=functools.partial(single_gpu_training, cfg, args),
          args=(iterations, results),
          nprocs=args.distributed_world_size,
          join=True,
      )
      return results
  
imports: import argparse
  import functools
  import random
  import unittest
  from multiprocessing import Manager
  import torch
  import torch.nn
  from omegaconf import OmegaConf
  from fairseq import optim
  from fairseq.distributed import utils
label_desc: Use image node_id 1 for calling the TestBMUF obj's underlying member method code with example usage: obj.bmuf_process(cfg, args, iterations) and returns: results