code: def test_maybe_set_distributed_sampler_epoch(self) -> None:
      config = get_pet_launch_config(2)
      launcher.elastic_launch(
          config,
          entrypoint=self._test_maybe_set_distributed_sampler_epoch,
      )()
  
imports: import unittest
  from typing import cast, Dict, Iterator
  import torch
  from torch import distributed, nn
  from torch.distributed import launcher
  from torch.utils.data import DataLoader
  from torch.utils.data.distributed import DistributedSampler
  from torchtnt.framework._loop_utils import _is_done, _is_epoch_done, _maybe_set_distributed_sampler_epoch, _reset_module_training_mode, _set_module_training_mode, _step_requires_iterator
  from torchtnt.framework._test_utils import generate_random_dataset
  from torchtnt.framework.state import State
  from torchtnt.utils.progress import Progress
  from torchtnt.utils.test_utils import get_pet_launch_config
label_desc: Use image node_id 1 for calling the LoopUtilsTest obj's underlying member method code with example usage: obj.test_maybe_set_distributed_sampler_epoch() without return types