code: def test_linear_row_wise_parallel(self):
      # test RowwiseParallel
      inp_size = [9, 16]
      rowwise = RowwiseParallel()
  
      torch.manual_seed(5)
      model = torch.nn.Linear(16, 10, device=self.device_type)
      torch.manual_seed(5)
      model_tp = torch.nn.Linear(16, 10, device=self.device_type)
  
      # parallelize model_tp
      device_mesh = DeviceMesh(
          self.device_type, list(range(self.world_size))
      )
      model_tp = parallelize_module(model_tp, device_mesh, rowwise)
  
      # let each rank generate unique local input
      torch.manual_seed(self.rank)
      self._compare_module(model, model_tp, inp_size, rowwise=True)
  
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 8 for calling the TensorParallelAPITests obj's underlying member method code with example usage: obj.test_linear_row_wise_parallel() without return types