code: def test_create_1d_device_mesh(self):
      dim_one_size = 2
      mesh_shape = (
          torch.arange(self.world_size)
          .reshape(
              self.world_size // dim_one_size,
              dim_one_size,
          )
          .to(torch.int)
      )
      mesh = DeviceMesh(self.device_type, mesh_shape)
      # When 1D dim is 1.
      one_dimention_mesh_shape = mesh_shape[
          self.rank // dim_one_size, :
      ]
      pg = mesh.get_group(mesh_dim=1)
      new_mesh = _create_1d_device_mesh(mesh, 1)
      expected_mesh = one_dimention_mesh_shape
  
      self.assertEqual(new_mesh.mesh, expected_mesh)
      self.assertEqual(new_mesh.device_type, self.device_type)
      self.assertEqual(new_mesh.get_group(), pg)
      # When 1D dim is 0.
      one_dimention_mesh_shape = mesh_shape[:, self.rank % dim_one_size]
      pg = mesh.get_group(mesh_dim=0)
      new_mesh = _create_1d_device_mesh(mesh, 0)
      expected_mesh = one_dimention_mesh_shape
      self.assertEqual(new_mesh.mesh, expected_mesh)
      self.assertEqual(new_mesh.device_type, self.device_type)
      self.assertEqual(new_mesh.get_group(), pg)
  
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 2 for calling the TensorParallelAPITests obj's underlying member method code with example usage: obj.test_create_1d_device_mesh() without return types