code: def test_transform_module_should_return_expected_transform(
      self, device, dtype
  ):
      torch.manual_seed(0)
      x_data = torch.rand(1, 2, 4, 5).to(device).type(dtype)
  
      expected_output = torch.tensor(
          [
              [
                  [
                      [0.0000, 0.0000, 0.0000, 0.0197, 0.0429],
                      [0.0000, 0.5632, 0.5322, 0.3677, 0.1430],
                      [0.0000, 0.3083, 0.4032, 0.1761, 0.0000],
                      [0.0000, 0.0000, 0.0000, 0.0000, 0.0000],
                  ],
                  [
                      [0.0000, 0.0000, 0.0000, 0.1189, 0.0586],
                      [0.0000, 0.7087, 0.5420, 0.3995, 0.0863],
                      [0.0000, 0.2695, 0.5981, 0.5888, 0.0000],
                      [0.0000, 0.0000, 0.0000, 0.0000, 0.0000],
                  ],
              ]
          ],
          device=device,
          dtype=x_data.dtype,
      )
  
      expected_transform = torch.tensor(
          [
              [
                  [1.0523, 0.3493, 0.3046],
                  [-0.1066, 1.0426, 0.5846],
                  [0.0351, 0.1213, 1.0000],
              ]
          ],
          device=device,
          dtype=x_data.dtype,
      )
  
      aug = kornia.augmentation.RandomPerspective(
          torch.tensor(0.5, device=device, dtype=dtype), p=0.99999999
      )  # step one the random state
  
      out_perspective = aug(x_data)
  
      assert out_perspective.shape == x_data.shape
      assert aug.transform_matrix.shape == (1, 3, 3)
      assert_close(
          out_perspective, expected_output, atol=1e-4, rtol=1e-4
      )
      assert_close(
          aug.transform_matrix, expected_transform, atol=1e-4, rtol=1e-4
      )
      assert aug.inverse(out_perspective).shape == x_data.shape
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 8 for calling the TestRandomPerspective obj's underlying member method code with example usage: obj.test_transform_module_should_return_expected_transform(device, dtype) without return types