code: def test_distributed_rank_logging(self):
      env = dict(os.environ)
      env["TORCH_LOGS"] = "dynamo"
      stdout, stderr = self.run_process_no_exception(
          """\
  import torch.distributed as dist
  import logging
  from torch.testing._internal.distributed.fake_pg import FakeStore
  store = FakeStore()
  dist.init_process_group("fake", rank=0, world_size=2, store=store)
  dynamo_log = logging.getLogger("torch._dynamo")
  dynamo_log.info("woof")
  print("arf")
  """,
          env=env,
      )
      self.assertIn("[rank0]:", stderr.decode("utf-8"))
  
imports: import atexit
  import contextlib
  import functools
  import logging
  import os
  import re
  import unittest.mock
  import torch
  import torch._dynamo.test_case
  import torch._dynamo.testing
  import torch.distributed
  from torch._dynamo.testing import skipIfNotPy311
  from torch.nn.parallel import DistributedDataParallel
  from torch.testing._internal.common_utils import find_free_port, munge_exc
  from torch.testing._internal.inductor_utils import HAS_CUDA
  from torch.testing._internal.logging_utils import LoggingTestCase, make_logging_test, make_settings_test
label_desc: Use image node_id 23 for calling the LoggingTests obj's underlying member method code with example usage: obj.test_distributed_rank_logging() without return types