code: def test_dtensor_device_mesh_device_conversion(self):
      # construct a cuda device mesh
      mesh = DeviceMesh(self.device_type, torch.arange(self.world_size))
  
      # construct from a cpu local tensor with cuda device mesh
      # should automatically convert the dist tensor to cuda
      placements = [Shard(0)]
      local_tensor = torch.randn(3, 3)
      dist_tensor = DTensor.from_local(local_tensor, mesh, placements)
      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 3 for calling the DTensorMeshTest obj's underlying member method code with example usage: obj.test_dtensor_device_mesh_device_conversion() without return types