code: def test_ones_like_partial_sum(self):
      device_mesh = DeviceMesh(
          self.device_type, list(range(self.world_size))
      )
      shard_spec = [_Partial()]
  
      input_tensor = torch.randn(4, 8, requires_grad=True)
      dist_tensor = DTensor.from_local(
          input_tensor, device_mesh, shard_spec
      )
      assert dist_tensor.shape == (4, 8)
  
      ones_like_dt = torch.ones_like(dist_tensor)
      ones_expected = torch.ones(dist_tensor.shape)
      self.assertEqual(ones_expected, ones_like_dt.full_tensor())
  
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 11 for calling the DistTensorOpsTest obj's underlying member method code with example usage: obj.test_ones_like_partial_sum() without return types