code: def test_prepare_module_output(self):
      module = DummyModule()
      device_mesh = DeviceMesh(
          self.device_type, list(range(self.world_size))
      )
      parallelize_module(
          module,
          device_mesh,
          PrepareModuleOutput(
              output_layouts=Replicate(),
              desired_output_layouts=Shard(0),
          ),
      )
      torch.manual_seed(15)
      inp = torch.rand(16, 7, device=self.device_type)
      dtensor = DTensor.from_local(
          inp, device_mesh, [Replicate()], run_check=False
      )
      output = module(dtensor)
      inp = dtensor.redistribute(device_mesh, [Shard(0)]).to_local()
      self.assertEqual(inp, output)
  
imports: from collections import OrderedDict
  import torch
  from torch.distributed._tensor import DeviceMesh, DTensor, Replicate, Shard
  from torch.distributed.tensor.parallel._utils import _create_1d_device_mesh
  from torch.distributed.tensor.parallel.api import parallelize_module
  from torch.distributed.tensor.parallel.style import ColwiseParallel, PrepareModuleInput, PrepareModuleOutput, RowwiseParallel
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, MLPModule, with_comms
label_desc: Use image node_id 11 for calling the TensorParallelAPITests obj's underlying member method code with example usage: obj.test_prepare_module_output() without return types