code: def test_complicated_dict(self):
      def create_dtensor():
          device_mesh = self.build_device_mesh()
          shard_spec = [Shard(0)]
          torch.random.manual_seed(dist.get_rank())
          local_tensor = torch.randn(3, 3, 3)
          dist_tensor = DTensor.from_local(
              local_tensor, device_mesh, shard_spec
          )
          tensor = funcol.all_gather_tensor(
              dist_tensor.to_local(),
              gather_dim=0,
              group=(device_mesh, 0),
          )
          return tensor, dist_tensor
  
      ltensor, ldtensor = [], []
      for i in range(10):
          tensor, dtensor = create_dtensor()
          ltensor.append(tensor)
          ltensor.append(torch.ones(10, device=torch.device("cuda")))
          ldtensor.append(dtensor)
          ldtensor.append(torch.ones(10, device=torch.device("cuda")))
  
      tensor, dtensor = create_dtensor()
      dist_state_dict = {
          "local": dtensor,
          "list": ldtensor,
          "arange": torch.arange(10, device=torch.device("cuda")),
      }
      state_dict = {
          "local": tensor,
          "list": ltensor,
          "arange": torch.arange(10, device=torch.device("cuda")),
      }
      self.assertEqual(state_dict, _gather_state_dict(dist_state_dict))
  
file_path: pytorch/test/distributed/checkpoint/test_state_dict_utils.py
imports: import torch
  import torch.distributed
  import torch.distributed._functional_collectives
  from torch.distributed._state_dict_utils import _gather_state_dict, _offload_state_dict_to_cpu
  from torch.distributed._tensor import DTensor
  from torch.distributed._tensor.placement_types import Shard
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, skip_if_lt_x_gpu, with_comms
label_desc: Use image node_id 5 for calling the TestStateDictUtils obj's underlying member method code with example usage: obj.test_complicated_dict() and returns: tensor,  dist_tensor