a828315185a9dc8b21ec8e5dbead9044caf0d3a2,test/geometry/warp/test_homography_warper.py,TestHomographyWarper,test_gradcheck,#TestHomographyWarper#Any#Any#,203

Before Change

        eye_size = 3  // identity 3x3

        // create checkerboard
        patch_src = torch.rand(batch_shape).to(device)
        patch_src = utils.tensor_to_gradcheck_var(patch_src)  // to var

        // create base homography
        batch_size, _, height, width = patch_src.shape
        dst_homo_src = utils.create_eye_batch(batch_size, eye_size).to(device)
        dst_homo_src = utils.tensor_to_gradcheck_var(
            dst_homo_src, requires_grad=False)  // to var

After Change

        assert_allclose(output, expected.to(device=device, dtype=dtype), atol=1e-4, rtol=1e-4)

    @pytest.mark.parametrize("height", [1, 2, 5])
    @pytest.mark.parametrize("width", [1, 2, 5])
    def test_divide_by_zero2d(self, height, width, device, dtype):
        output = kornia.normal_transform_pixel(height, width, device=device, dtype=dtype)
        assert torch.isinf(output).sum().item() == 0

    def test_transform2d_apply(self, device, dtype):

Instances