code: def _run(cls, rank, test_name, file_name, pipe):
      self = cls(test_name)
      self.assertTrue(torch.cuda.is_available())
      self.assertTrue(hasattr(self, "DISTRIBUTED_BACKEND"))
      self.rank = rank
      self.file_name = file_name
  
      print(
          f"[dist init] rank = {self.rank}, world_size = {self.world_size}"
      )
  
      try:
          dist.init_process_group(
              init_method=self.init_method,
              backend=self.DISTRIBUTED_BACKEND,
              world_size=int(self.world_size),
              rank=self.rank,
          )
      except RuntimeError as e:
          if "recompile" in e.args[0]:
              print(
                  f"Backend of {self.DISTRIBUTED_BACKEND} not available"
              )
              sys.exit(0)
          raise
  
      torch.cuda.set_device(self.rank % torch.cuda.device_count())
  
      dist.barrier()
      self.run_test(test_name, pipe)
      dist.barrier()
  
      dist.destroy_process_group()
      sys.exit(0)
  
imports: import os
  import sys
  import unittest
  from packaging.version import Version, parse
  import torch
  from torch import distributed
  from torch.utils import collect_env
  from torch.testing._internal import common_utils
  from torch.testing._internal import common_distributed
  from apex.transformer._ucc_util import HAS_UCC
label_desc: Use image node_id 6 for calling the DistributedTestBase obj's underlying member method code with example usage: obj._run(cls, rank, test_name, file_name, pipe) without return types