def test_gradcheck(self, device, dtype): B, C, H, W = 2, 3, 4, 4 img = torch.rand(B, C, H, W, device=device, dtype=torch.float64, requires_grad=True) img = kornia.rgb_to_luv(img) assert gradcheck(kornia.color.luv_to_rgb, (img, ), raise_exception=True)
def test_grad(self, device): data = kornia.rgb_to_luv(torch.rand(2, 3, 4, 5).to(device)) data = utils.tensor_to_gradcheck_var(data) assert gradcheck(kornia.color.LuvToRgb(), (data, ), raise_exception=True)