code: def test_dtensor_api_device_mesh_context_manager(self):
      with DeviceMesh(
          self.device_type, list(range(self.world_size))
      ) as mesh:
          placements = [Shard(0)]
          local_tensor = torch.randn(3, 3)
          sharded_tensor = DTensor.from_local(
              local_tensor, device_mesh=mesh, placements=placements
          )
  
      with DeviceMesh(self.device_type, list(range(self.world_size))):
          placements = [Shard(0)]
          local_tensor = torch.randn(3, 3)
          sharded_tensor = DTensor.from_local(
              local_tensor, placements=placements
          )
          replica_spec = [Replicate()]
          replica_tensor = sharded_tensor.redistribute(
              placements=replica_spec
          )
          self.assertEqual(
              replica_tensor.size(),
              torch.Size([3 * self.world_size, 3]),
          )
  
      with DeviceMesh(self.device_type, torch.arange(self.world_size)):
          placements = [Shard(0)]
          global_shape = torch.Size([3 * self.world_size, 3])
          global_tensor = torch.randn(global_shape)
          sharded_tensor = distribute_tensor(
              global_tensor, placements=placements
          )
          self.assertEqual(
              sharded_tensor.to_local().shape, torch.Size([3, 3])
          )
  
          mesh_2d = DeviceMesh(
              self.device_type,
              torch.arange(self.world_size).reshape(2, 4),
          )
  
          with mesh_2d:
              shard_2d_spec = [Shard(0), Replicate()]
              tensor_2d = distribute_tensor(
                  global_tensor, placements=shard_2d_spec
              )
  
              self.assertEqual(
                  tensor_2d.to_local().shape, torch.Size([3 * 4, 3])
              )
  
          sharded_after_2d = distribute_tensor(
              global_tensor, placements=placements
          )
          self.assertEqual(
              sharded_after_2d.to_local().shape, torch.Size([3, 3])
          )
  
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 4 for calling the DTensorMeshTest obj's underlying member method code with example usage: obj.test_dtensor_api_device_mesh_context_manager() without return types