PaddlePaddle/GraphNet
Nov 2025 – Dec 2025
2 Months active
Languages Used
Pythonbash
Technical Skills
PyTorchbash scriptingmachine learningsoftware engineeringtestingunit testing
AKatydid
PROFILE
Akatydid
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
1
Lines of code
309
Activity Months2
Your Network
21 people
Work History
December 2025
1 Commits
Dec 1, 2025December 2025 monthly summary for PaddlePaddle/GraphNet focused on resolving a critical tensor metadata device attribute handling issue to improve device compatibility. The fix ensures the device attribute is correctly set in tensor metadata, reducing device-related errors and increasing stability across hardware configurations. Implemented via commit ddc026b5931e2e0e6e5c941ca9742c7b56d07983 with message 'fix: not apply tensor in tensor_meta (#463)'.
1 Commits
Dec 1, 2025December 2025 monthly summary for PaddlePaddle/GraphNet focused on resolving a critical tensor metadata device attribute handling issue to improve device compatibility. The fix ensures the device attribute is correctly set in tensor metadata, reducing device-related errors and increasing stability across hardware configurations. Implemented via commit ddc026b5931e2e0e6e5c941ca9742c7b56d07983 with message 'fix: not apply tensor in tensor_meta (#463)'.
December 2025
November 2025
2 Commits • 1 Features
Nov 1, 2025Performance-focused monthly summary for PaddlePaddle/GraphNet (2025-11): Delivered modular graph extraction enhancements via submodule folding, strengthened testing coverage, and refactored core utilities to improve maintainability. Fixed configuration parsing in tests to increase reliability of test runs. Overall, these changes reduced maintenance cost, accelerated validation, and strengthened the product's modular architecture.
November 2025
2 Commits • 1 Features
Nov 1, 2025Performance-focused monthly summary for PaddlePaddle/GraphNet (2025-11): Delivered modular graph extraction enhancements via submodule folding, strengthened testing coverage, and refactored core utilities to improve maintainability. Fixed configuration parsing in tests to increase reliability of test runs. Overall, these changes reduced maintenance cost, accelerated validation, and strengthened the product's modular architecture.
Activity
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Quality Metrics
Correctness93.4%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Pythonbash
Technical Skills
PyTorchbash scriptingdata processingmachine learningsoftware engineeringtestingunit testing
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