code: def _create_tensor(self, size):
      # Keep everything deterministic.
      torch.manual_seed(0)
      tensor = torch.rand(size)
      if self.device_type == "cuda":
          return tensor.cuda()
      else:
          return tensor
  
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 2 for calling the TestDTensorPlacementTypes obj's underlying member method code with example usage: obj._create_tensor(size) and returns: tensor, tensor