code: def test_fsspec_no_dist(self) -> None:
      with tempfile.TemporaryDirectory() as path:
          state_dict_to_save = MyTestModule().state_dict()
  
          dcp.save_state_dict(
              state_dict=state_dict_to_save,
              storage_writer=FsspecWriter(path),
              no_dist=True,
          )
  
          state_dict_to_load_to = MyTestModule().state_dict()
  
          for p1, p2 in zip(
              state_dict_to_save.items(),
              state_dict_to_load_to.items(),
          ):
              self.assertNotEqual(p1, p2)
  
          # Load from file without any resharding
          dcp.load_state_dict(
              state_dict=state_dict_to_load_to,
              storage_reader=FsspecReader(path),
              no_dist=True,
          )
  
          for p1, p2 in zip(
              state_dict_to_save.items(),
              state_dict_to_load_to.items(),
          ):
              self.assertEqual(p1, p2)
  
imports: import shutil
  import tempfile
  from functools import wraps
  from typing import Any, Callable, Dict, Optional, Tuple
  import torch
  import torch.distributed
  import torch.distributed.checkpoint
  import torch.nn
  from torch.distributed.checkpoint._fsspec_filesystem import FsspecReader, FsspecWriter
  from torch.distributed.checkpoint.optimizer import load_sharded_optimizer_state_dict
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed.fsdp.fully_sharded_data_parallel import StateDictType
  from torch.testing._internal.common_distributed import requires_nccl, skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import run_tests, TestCase
  from torch.testing._internal.distributed._shard.sharded_tensor import ShardedTensorTestBase, with_comms
label_desc: Use image node_id 1 for calling the TestFSSpecNoDist obj's underlying member method code with example usage: obj.test_fsspec_no_dist() without return types