pytorch/executorch
Oct 2024 – Oct 2024
1 Month active
Languages Used
C++Python
Technical Skills
C++ developmentCMakePythonbackend developmentloggingperformance optimization
Zonglin Peng
PROFILE
Zonglin Peng
Worked on the pytorch/executorch repository to enhance reliability and modularity by refactoring quant-per-tensor HiFi operations into a new open-source namespace, which streamlined imports and improved code organization. Addressed two critical bugs by ensuring proper namespace access for HiFi operator functions and resolving an issue where the runtime executor produced empty outputs on the CPU path. These changes included adding missing dependencies and enabling runtime logging for better debugging and future scalability. Utilized C++ and Python, along with CMake for build management, focusing on backend development, logging improvements, and performance optimization to lay groundwork for ongoing and future enhancements.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
102
Activity Months1
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3160 peopleSame Organization
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Aaryaman SagarMember
Aashay GaikwadMember
Ajanthan AsogamoorthyMember
Work History
October 2024
3 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on reliability, modularity, and enabling future-scale for the executorch codebase through targeted bug fixes and a namespace refactor.
3 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Focused on reliability, modularity, and enabling future-scale for the executorch codebase through targeted bug fixes and a namespace refactor.
October 2024
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage33.4%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ developmentCMakePythonbackend developmentloggingperformance optimization
Repositories Contributed To
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