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(
          [
              [
                  [
                      [
                          0.0042,
                          0.0054,
                          0.0035,
                          0.0006,
                          0.0035,
                          0.0054,
                          0.0042,
                      ],
                      [
                          0.0054,
                          0.0068,
                          0.0046,
                          0.0014,
                          0.0046,
                          0.0068,
                          0.0054,
                      ],
                      [
                          0.0035,
                          0.0046,
                          0.0034,
                          0.0014,
                          0.0034,
                          0.0046,
                          0.0035,
                      ],
                      [
                          0.0006,
                          0.0014,
                          0.0014,
                          0.0006,
                          0.0014,
                          0.0014,
                          0.0006,
                      ],
                      [
                          0.0035,
                          0.0046,
                          0.0034,
                          0.0014,
                          0.0034,
                          0.0046,
                          0.0035,
                      ],
                      [
                          0.0054,
                          0.0068,
                          0.0046,
                          0.0014,
                          0.0046,
                          0.0068,
                          0.0054,
                      ],
                      [
                          0.0042,
                          0.0054,
                          0.0035,
                          0.0006,
                          0.0035,
                          0.0054,
                          0.0042,
                      ],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      ).float()
      harris = kornia.feature.CornerHarris(k=0.04).to(device)
      scores = harris(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 TestCornerHarris obj's underlying member method code with example usage: obj.test_corners(device, dtype) without return types