code: def dist_init(self, rank, world_size=-1, backend=BACKEND):
      if world_size < 1:
          world_size = self.world_size
      store = dist.FileStore(self.file_name, world_size)
      return dist.init_process_group(
          backend=backend,
          store=store,
          rank=rank,
          world_size=world_size,
      )
  
imports: import copy
  import os
  import sys
  import unittest
  from contextlib import nullcontext
  from typing import Any, cast, List
  import numpy
  import torch
  import torch.distributed
  from torch.distributed.algorithms.ddp_comm_hooks.ddp_zero_hook import hook_with_zero_step, hook_with_zero_step_interleaved
  from torch.distributed.algorithms.ddp_comm_hooks.default_hooks import allreduce_hook
  from torch.distributed.algorithms.join import Join, Joinable, JoinHook
  from torch.distributed.optim import ZeroRedundancyOptimizer
  from torch.distributed.optim.zero_redundancy_optimizer import _broadcast_object
  from torch.nn.parallel import DistributedDataParallel
  from torch.optim import AdamW, SGD
  from torch.testing._internal import common_distributed
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, IS_WINDOWS, parametrize, run_tests, TEST_WITH_ASAN, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 5 for calling the TestZeroRedundancyOptimizer obj's underlying member method code with example usage: obj.dist_init(rank, world_size, backend) and returns: dist