7634391b070859dc1c11b092fde754dbc7911d4a,test/test_losses.py,TestSSIMLoss,test_ssim,#TestSSIMLoss#,280

Before Change

    @pytest.mark.parametrize("batch_shape", [(1, 1, 10, 16), (2, 4, 8, 15)])
    def test_ssim(self, device, batch_shape, window_size, reduction_type):
        // input data
        img = torch.rand(batch_shape).to(device)

        ssim = kornia.losses.SSIM(window_size, reduction_type)
        assert_allclose(ssim(img, img).item(), 0.0)

After Change

        ssim = kornia.losses.SSIM(window_size, reduction_type)
        loss = ssim(img, img)

        tol_val: float = utils._get_precision_by_name(device, "xla", 1e-1, 1e-4)
        assert_allclose(loss.item(), 0.0, rtol=tol_val, atol=tol_val)

    def test_gradcheck(self, device, dtype):
        // input data

Instances