code: def test_toy(self, device, dtype):
      inp = torch.zeros(1, 1, 33, 33, device=device, dtype=dtype)
      inp[:, :, 13:-13, 13:-13] = 1.0
      n_feats = 1
      det = ScaleSpaceDetector(
          n_feats, resp_module=kornia.feature.BlobHessian(), mr_size=3.0
      ).to(device, dtype)
      lafs, resps = det(inp)
      expected_laf = torch.tensor(
          [[[[9.5823, 0.0000, 16.0], [0.0, 9.5823, 16.0]]]],
          device=device,
          dtype=dtype,
      )
      expected_resp = torch.tensor(
          [[0.0857]], device=device, dtype=dtype
      )
      assert_close(lafs, expected_laf, rtol=0.001, atol=1e-03)
      assert_close(resps, expected_resp, rtol=0.001, atol=1e-03)
  
file_path: kornia/test/feature/test_scale_space_detector.py
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.feature.scale_space_detector import ScaleSpaceDetector
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestScaleSpaceDetector obj's underlying member method code with example usage: obj.test_toy(device, dtype) without return types