pymc-devs/pytensor
May 2025 – May 2025
1 Month active
Languages Used
JAXNumPyPython
Technical Skills
Code RefactoringJAXLinear AlgebraNumerical ComputingNumerical MethodsScientific Computing
Ben F. Maier
PROFILE
Ben F. Maier
Worked on the JAX Tridiagonal Solver within the pymc-devs/pytensor repository, focusing on improving shape compatibility and input handling for both 1D and 2D right-hand sides. Addressed issues with diagonal padding and ensured that output shapes consistently matched input dimensions, including automatic expansion of 1D vectors to columns when necessary. Enhanced reliability by expanding test coverage to include both vector and matrix cases, and refactored tests for clarity and maintainability. Utilized Python, JAX, and NumPy, applying skills in code refactoring, numerical computing, and scientific testing to reduce regression risk and support robust probabilistic modeling workflows for users.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
1
Lines of code
150
Activity Months1
Your Network
50 peopleShared Repositories
50
Work History
May 2025
5 Commits • 1 Features
May 1, 2025May 2025: Focused improvements to the JAX Tridiagonal Solver in pytensor, delivering shape-correctness fixes and expanded test coverage. Outcomes include robust handling for 1D and 2D RHS, proper padding of diagonals, and regression-proof tests for vector and matrix RHS. These changes increase reliability for users building probabilistic models with JAX, improve maintainability, and reduce risk of future regressions.
5 Commits • 1 Features
May 1, 2025May 2025: Focused improvements to the JAX Tridiagonal Solver in pytensor, delivering shape-correctness fixes and expanded test coverage. Outcomes include robust handling for 1D and 2D RHS, proper padding of diagonals, and regression-proof tests for vector and matrix RHS. These changes increase reliability for users building probabilistic models with JAX, improve maintainability, and reduce risk of future regressions.
May 2025
Activity
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Quality Metrics
Correctness94.0%
Maintainability92.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JAXNumPyPython
Technical Skills
Code RefactoringJAXLinear AlgebraNumerical ComputingNumerical MethodsScientific ComputingTesting
Repositories Contributed To
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