code: def test_redistribute_sub_mesh(self):
      mesh = DeviceMesh(self.device_type, [0, 2])
  
      # test redistribute on a submesh
      local_tensor1 = torch.ones(4, 3)
      sharded_dtensor = DTensor.from_local(
          local_tensor1, mesh, [Shard(0)]
      )
      replicated_dtensor = sharded_dtensor.redistribute(
          placements=[Replicate()]
      )
      self.sub_mesh_assert_equal(
          mesh.mesh,
          torch.ones(8, 3),
          torch.tensor([]),
          replicated_dtensor.to_local(),
      )
      sharded_again = replicated_dtensor.redistribute(
          placements=[Shard(0)]
      )
      self.sub_mesh_assert_equal(
          mesh.mesh,
          torch.ones(4, 3),
          torch.tensor([]),
          sharded_again.to_local(),
      )
  
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 10 for calling the DTensorMeshTest obj's underlying member method code with example usage: obj.test_redistribute_sub_mesh() without return types