code: def test_device_mesh_nd(self):
      # construct a cuda device mesh
      mesh_tensor = torch.arange(self.world_size).reshape(2, 2, 2)
      mesh = DeviceMesh(self.device_type, mesh_tensor)
      # construct a dist tensor on 3d device mesh and test if works
      placements = [Shard(0), Shard(1), Shard(2)]
      local_tensor = torch.randn(3, 3, 3)
      dist_tensor = DTensor.from_local(local_tensor, mesh, placements)
      self.assertEqual(dist_tensor.size(), torch.Size([6, 6, 6]))
      self.assertEqual(dist_tensor.device.type, self.device_type)
      self.assertEqual(
          dist_tensor.to_local().device.type, self.device_type
      )
  
      # construct a dist tensor on 3d device mesh with some shards on same dim
      placements = [Shard(0), Shard(0), Shard(2)]
      local_tensor = torch.randn(3, 3, 3)
      dist_tensor = DTensor.from_local(local_tensor, mesh, placements)
      self.assertEqual(dist_tensor.size(), torch.Size([12, 3, 6]))
      self.assertEqual(dist_tensor.device.type, self.device_type)
      self.assertEqual(
          dist_tensor.to_local().device.type, self.device_type
      )
  
imports: import torch
  import torch.nn.functional
  from numpy.testing import assert_array_equal
  from torch.distributed._functional_collectives import AsyncCollectiveTensor
  from torch.distributed._tensor import DeviceMesh, distribute_tensor, DTensor, init_device_mesh
  from torch.distributed._tensor.placement_types import _Partial, Replicate, Shard
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, RowwiseParallel
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, with_comms
label_desc: Use image node_id 6 for calling the DTensorMeshTest obj's underlying member method code with example usage: obj.test_device_mesh_nd() without return types