pytorch/executorch
Oct 2024 – Oct 2024
1 Month active
Languages Used
C++Python
Technical Skills
C++ developmentCMakePythonbackend developmentloggingperformance optimization
Zonglin Peng
PROFILE
Zonglin Peng
Zonglin Peng contributed to the pytorch/executorch repository by enhancing reliability and modularity in the codebase. He migrated quant-per-tensor HiFi operations to a new open-source namespace, addressing import issues and laying groundwork for future scalability. Using C++ and CMake, Zonglin fixed a namespace access bug in HiFi operator files and resolved a CPU path issue that previously led to empty outputs, adding missing dependencies and enabling runtime logging for better debugging. His work focused on backend development and performance optimization, resulting in clearer logging, improved dependency management, and a more maintainable architecture within the executorch project during the month.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
3Total
Bugs
2
Commits
3
Features
1
Lines of code
102
Activity Months1
Your Network
2539 people
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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