Fix quaternion gradient accumulation in GaussianProjectionJaggedBackward#534
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…JaggedBackward kernel Signed-off-by: Jonathan Swartz <jonathan@jswartz.info>
…ting - Introduced `TestProjectionGradsMultiCamera` to verify correct summation of Gaussian parameter gradients across multiple cameras during the projection backward pass. - Implemented tests for both dense and jagged paths, ensuring gradients are accurately computed and compared against independent single-camera renders. Signed-off-by: Jonathan Swartz <jonathan@jswartz.info>
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Mar 11, 2026
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This pull request introduces a new unit test to verify that Gaussian parameter gradients are correctly accumulated across multiple cameras in the projection backward pass, addressing a potential issue with warp-level reductions. It also includes a minor fix in the GaussianProjectionJaggedBackward kernel to ensure proper gradient accumulation for quaternions. The changes are grouped below by theme.
Testing improvements:
TestProjectionGradsMultiCameratest class totests/unit/test_gaussian_splat_3d.py, which verifies that gradients for all Gaussian parameters are correctly summed across cameras in both dense and jagged projection backward passes. This test ensures that warp-level reductions (warpSum) do not drop camera contributions, preventing silent bugs when multiple cameras share a warp for the same Gaussian.CUDA kernel fix:
src/fvdb/detail/ops/gsplat/GaussianProjectionJaggedBackward.cuby adding awarpSumcall for quaternion gradients (dLossDQuat), ensuring all camera contributions are properly accumulated in the jagged projection backward kernel.