pytorch/executorch
Oct 2024 – Oct 2024
1 Month active
Languages Used
C++Python
Technical Skills
Python programmingdeep learningmachine learningmodel optimizationquantization
haowhsu-quic
PROFILE
Haowhsu-quic
During October 2024, Hao Hsu enabled open-source FastViT model support within the Qualcomm AI Engine for the pytorch/executorch repository. He addressed tensor shape mismatches during layout transformations by developing a dedicated pass, ensuring robust model integration. To further enhance reliability, Hao implemented a ParamObserver that detects and manages outlier parameters, contributing to model stability. His work involved targeted refactoring and bug fixes, focusing on seamless OSS model enablement. Leveraging Python and C++ alongside deep learning and model optimization expertise, Hao delivered a technically thorough solution that improved the integration and operational robustness of FastViT within the Qualcomm AI Engine environment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,118
Activity Months1
Your Network
466 people
Work History
October 2024
1 Commits • 1 Features
Oct 1, 2024Month: 2024-10 highlights the delivery of OSS model enablement for FastViT in the Qualcomm AI Engine for the pytorch/executorch repo. Key work includes a new pass to handle tensor shape mismatches during layout transformations, a ParamObserver to track outlier parameters, and targeted refactoring plus bug fixes to stabilize the OSS enablement and integration.
1 Commits • 1 Features
Oct 1, 2024Month: 2024-10 highlights the delivery of OSS model enablement for FastViT in the Qualcomm AI Engine for the pytorch/executorch repo. Key work includes a new pass to handle tensor shape mismatches during layout transformations, a ParamObserver to track outlier parameters, and targeted refactoring plus bug fixes to stabilize the OSS enablement and integration.
October 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
Python programmingdeep learningmachine learningmodel optimizationquantization
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