PaddlePaddle/Paddle2ONNX
Oct 2024 – Nov 2024
2 Months active
Languages Used
C++Python
Technical Skills
C++Model ConversionONNXPIRPaddlePaddlePython
qzylalala
PROFILE
Qzylalala
Over two months, this developer expanded Paddle-PIR operator support and improved model export workflows in the PaddlePaddle/Paddle2ONNX repository. They implemented new operator mappings and exporter updates in C++ and Python, enabling broader compatibility for PIR-mode model conversion to ONNX. Their work included adding support for core operators such as cumsum, gather_nd, interpolate, and various tensor operations, while also addressing bugs in tensor value retrieval to enhance runtime stability. By increasing test coverage and refining exporter logic, they reduced manual intervention and improved translation fidelity, laying a foundation for more efficient, scalable, and reliable Paddle-to-ONNX model deployment.
Overall Statistics
Feature vs Bugs
88%Features
Repository Contributions
27Total
Bugs
2
Commits
27
Features
14
Lines of code
1,900
Activity Months2
Your Network
8 people
Work History
November 2024
22 Commits • 13 Features
Nov 1, 2024November 2024 performance for Paddle2ONNX focused on expanding PIR operator coverage and stabilizing tensor handling to accelerate Paddle-to-ONNX model exports and improve runtime reliability. Delivered initial core PIR operator support, added comprehensive cumulative sum (cumsum) support, introduced gather_nd, interpolate, and additional PIR operations, and completed critical bug fixes to improve tensor value retrieval. These changes increase translation fidelity, reduce manual intervention, and enable broader model support with improved test coverage. This work lays the foundation for more efficient and scalable ONNX export workflows and downstream optimization, driving faster time-to-value for customers deploying Paddle models through ONNX.
22 Commits • 13 Features
Nov 1, 2024November 2024 performance for Paddle2ONNX focused on expanding PIR operator coverage and stabilizing tensor handling to accelerate Paddle-to-ONNX model exports and improve runtime reliability. Delivered initial core PIR operator support, added comprehensive cumulative sum (cumsum) support, introduced gather_nd, interpolate, and additional PIR operations, and completed critical bug fixes to improve tensor value retrieval. These changes increase translation fidelity, reduce manual intervention, and enable broader model support with improved test coverage. This work lays the foundation for more efficient and scalable ONNX export workflows and downstream optimization, driving faster time-to-value for customers deploying Paddle models through ONNX.
November 2024
October 2024
5 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Paddle2ONNX: Paddle-PIR to ONNX operator support expansion and exporter mappings. Delivered broader PIR-mode compatibility via new operator mappings and exporter updates; strengthened tests and stability for production exports.
October 2024
5 Commits • 1 Features
Oct 1, 2024Month: 2024-10 — Paddle2ONNX: Paddle-PIR to ONNX operator support expansion and exporter mappings. Delivered broader PIR-mode compatibility via new operator mappings and exporter updates; strengthened tests and stability for production exports.
Activity
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Quality Metrics
Correctness86.2%
Maintainability85.8%
Architecture84.4%
Performance74.2%
AI Usage20.8%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++C++ DevelopmentCI/CDCode RefactoringCompiler DevelopmentDeep Learning FrameworksFramework IntegrationInference RuntimeMachine Learning OperationsMapper DevelopmentModel ConversionONNXONNX ConversionOperator MappingPIR
Repositories Contributed To
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