code: def test_t(self):
      device_mesh = DeviceMesh(
          self.device_type, list(range(self.world_size))
      )
      shard_spec = [Shard(0)]
  
      tensor_to_transpose = torch.randn(12, 8, requires_grad=True)
      mat = distribute_tensor(
          tensor_to_transpose, device_mesh, shard_spec
      )
      tranposed_mat = mat.t()
      self.assertEqual(tranposed_mat.size(), torch.Size([8, 12]))
      self.assertEqual(tranposed_mat.placements, [Shard(1)])
      tranposed_mat2 = tranposed_mat.t()
      self.assertEqual(tranposed_mat2.size(), torch.Size([12, 8]))
      self.assertEqual(tranposed_mat2.placements, shard_spec)
  
file_path: pytorch/test/distributed/_tensor/test_matrix_ops.py
imports: import itertools
  from typing import cast, List, Optional
  import torch
  from torch.distributed._tensor import DeviceMesh, distribute_tensor
  from torch.distributed._tensor.api import DTensor
  from torch.distributed._tensor.placement_types import _Partial, Placement, Replicate, Shard
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, skip_unless_torch_gpu, with_comms
label_desc: Use image node_id 4 for calling the DistMatrixOpsTest obj's underlying member method code with example usage: obj.test_t() without return types