code: def test_corners(self, device, dtype):
      inp = torch.tensor(
          [
              [
                  [
                      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
                      [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0],
                      [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0],
                      [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0],
                      [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0],
                      [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0],
                      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      ).float()
  
      expected = torch.tensor(
          [
              [
                  [
                      [
                          0.0379,
                          0.0456,
                          0.0283,
                          0.0121,
                          0.0283,
                          0.0456,
                          0.0379,
                      ],
                      [
                          0.0456,
                          0.0598,
                          0.0402,
                          0.0168,
                          0.0402,
                          0.0598,
                          0.0456,
                      ],
                      [
                          0.0283,
                          0.0402,
                          0.0545,
                          0.0245,
                          0.0545,
                          0.0402,
                          0.0283,
                      ],
                      [
                          0.0121,
                          0.0168,
                          0.0245,
                          0.0276,
                          0.0245,
                          0.0168,
                          0.0121,
                      ],
                      [
                          0.0283,
                          0.0402,
                          0.0545,
                          0.0245,
                          0.0545,
                          0.0402,
                          0.0283,
                      ],
                      [
                          0.0456,
                          0.0598,
                          0.0402,
                          0.0168,
                          0.0402,
                          0.0598,
                          0.0456,
                      ],
                      [
                          0.0379,
                          0.0456,
                          0.0283,
                          0.0121,
                          0.0283,
                          0.0456,
                          0.0379,
                      ],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      ).float()
      shi_tomasi = kornia.feature.CornerGFTT().to(device)
      scores = shi_tomasi(inp)
      assert_close(scores, expected, atol=1e-4, rtol=1e-3)
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestCornerGFTT obj's underlying member method code with example usage: obj.test_corners(device, dtype) without return types