code: def test_shape(self, device):
      inp = torch.rand(1, 1, 32, 32, device=device)
      laf = torch.rand(1, 1, 2, 3, device=device)
      ori = LAFAffNetShapeEstimator(False).to(device).eval()
      out = ori(laf, inp)
      assert out.shape == laf.shape
  
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 1 for calling the TestLAFAffNetShapeEstimator obj's underlying member method code with example usage: obj.test_shape(device) without return types