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)