code: def test_single_gpu_bmuf(self):
      # Train model for 5 iterations and use GPU 1
      cfg, args = setup_args()
      args.distributed_world_size = 1
      args.warmup_iterations = 5
      cfg.distributed_training.distributed_world_size = (
          args.distributed_world_size
      )
      cfg.bmuf.distributed_world_size = args.distributed_world_size
      cfg.bmuf.warmup_iterations = args.warmup_iterations
      iterations = 20
      results = self.bmuf_process(cfg, args, iterations)
      assert len(results) == 1
  
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 5 for calling the TestBMUF obj's underlying member method code with example usage: obj.test_single_gpu_bmuf() without return types