code: def test_inplace_op(self):
      mesh = DeviceMesh(self.device_type, list(range(self.world_size)))
      input_tensor = torch.randn((12, 3), device=self.device_type)
      dt_to_add = distribute_tensor(input_tensor, mesh, [Shard(0)])
      dt_to_mul = dt_to_add.clone()
      expected_add_dt = dt_to_add.clone() + 3
      add_res = dt_to_add.add_(3)
      expected_mul_dt = dt_to_mul.clone() * 3
      mul_res = dt_to_mul.mul_(3)
      # inplace op should be the same instance before and after
      self.assertTrue(add_res is dt_to_add)
      self.assertEqual(add_res.to_local(), expected_add_dt.to_local())
  
      self.assertTrue(mul_res is dt_to_mul)
      self.assertEqual(mul_res.to_local(), expected_mul_dt.to_local())
  
      # test inplace op self and other dtensor with other specs
      # and make sure out spec not change
      shard_spec = [Shard(0)]
      partial_spec = [_Partial()]
      dt_to_inplace_add = distribute_tensor(
          input_tensor, mesh, shard_spec
      )
      partial_grad = DTensor.from_local(
          torch.randn(12, 3), mesh, partial_spec
      )
      res = dt_to_inplace_add.add_(partial_grad)
      self.assertTrue(res is dt_to_inplace_add)
      self.assertTrue(res.placements == tuple(shard_spec))
  
imports: import torch
  from torch.distributed._tensor import DeviceMesh, distribute_tensor, DTensor
  from torch.distributed._tensor.placement_types import _Partial, Replicate, Shard
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorConverter, DTensorTestBase, with_comms
label_desc: Use image node_id 5 for calling the DistTensorOpsTest obj's underlying member method code with example usage: obj.test_inplace_op() without return types