code: def test_clone(self):
      device_mesh = DeviceMesh(
          self.device_type, list(range(self.world_size))
      )
      specs = [[Replicate()], [Shard(0)]]
      tensor_to_clone = torch.randn(12, 8, requires_grad=True)
      for spec in specs:
          mat = distribute_tensor(tensor_to_clone, device_mesh, spec)
          cloned_mat = mat.clone()
          self.assertFalse(cloned_mat is mat)
          self.assertEqual(cloned_mat.to_local(), mat.to_local())
  
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 3 for calling the DistTensorOpsTest obj's underlying member method code with example usage: obj.test_clone() without return types