intel/torch-xpu-ops
May 2026 – Jun 2026
2 Months active
Languages Used
C++Python
Technical Skills
C++ developmentGPU programmingPythonPython developmentSparse matrix operationsUnit testing
Jakub Kosno
PROFILE
Jakub Kosno
Worked on the intel/torch-xpu-ops repository to deliver core SparseXPU functionality and improve test suite stability for XPU devices. Developed and integrated sparse matrix multiplication support by implementing aten::hspmm and hspmm.out, using C++ and Python to extend SparseTensorMath kernels and dispatch registrations. Enhanced test coverage and reliability by adding targeted XPU tests, skipping flaky or deprecated TorchScript-related cases, and aligning test expectations with actual backend behavior. Focused on maintainability by excluding unsupported tests and clarifying the impact of TorchScript deprecation, resulting in a more robust CI process and smoother onboarding for PyTorch XPU backend development workflows.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
1
Lines of code
180
Activity Months2
Your Network
2328 peopleSame Organization
@intel.com2260
Work History
June 2026
1 Commits
Jun 1, 2026June 2026 monthly work summary for intel/torch-xpu-ops: Focused on stabilizing the XPU test suite in the face of TorchScript deprecation, delivering a targeted change to exclude failing tests that are not implemented for XPU. This improved CI reliability and feedback velocity, aligning test coverage with the current capabilities of the XPU backend and TorchScript timeline.
1 Commits
Jun 1, 2026June 2026 monthly work summary for intel/torch-xpu-ops: Focused on stabilizing the XPU test suite in the face of TorchScript deprecation, delivering a targeted change to exclude failing tests that are not implemented for XPU. This improved CI reliability and feedback velocity, aligning test coverage with the current capabilities of the XPU backend and TorchScript timeline.
June 2026
May 2026
3 Commits • 1 Features
May 1, 2026May 2026 performance summary for intel/torch-xpu-ops focusing on delivering core SparseXPU capabilities, stabilizing the test suite, and aligning tests with actual XPU behavior to accelerate release readiness.
May 2026
3 Commits • 1 Features
May 1, 2026May 2026 performance summary for intel/torch-xpu-ops focusing on delivering core SparseXPU capabilities, stabilizing the test suite, and aligning tests with actual XPU behavior to accelerate release readiness.
Activity
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Quality Metrics
Correctness95.0%
Maintainability85.0%
Architecture85.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ developmentGPU programmingPyTorchPythonPython developmentSparse matrix operationsTestingUnit testingXPUbug fixingdata processingnumerical computingtesting
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