code: def test_toy(self, device, dtype):
      aff = LAFAffNetShapeEstimator(True).to(device, dtype).eval()
      inp = torch.zeros(1, 1, 32, 32, device=device, dtype=dtype)
      inp[:, :, 15:-15, 9:-9] = 1
      laf = torch.tensor(
          [[[[20.0, 0.0, 16.0], [0.0, 20.0, 16.0]]]],
          device=device,
          dtype=dtype,
      )
      new_laf = aff(laf, inp)
      expected = torch.tensor(
          [[[[33.2073, 0.0, 16.0], [-1.3766, 12.0456, 16.0]]]],
          device=device,
          dtype=dtype,
      )
      assert_close(new_laf, expected, atol=1e-4, rtol=1e-4)
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia.testing
  from kornia.feature.affine_shape import LAFAffineShapeEstimator, LAFAffNetShapeEstimator, PatchAffineShapeEstimator
  from kornia.testing import assert_close
label_desc: Use image node_id 5 for calling the TestLAFAffNetShapeEstimator obj's underlying member method code with example usage: obj.test_toy(device, dtype) without return types