
In March 2025, Chris Rhodes developed PyTorch support for the sympy/sympy repository, enabling symbolic expressions in SymPy to be converted directly into PyTorch code. He implemented a TorchPrinter and extended lambdify functionality, allowing seamless integration between symbolic mathematics and machine learning workflows. Using Python and YAML, Chris refactored the PyTorch printing logic, improved test coverage, and reorganized packaging to ensure reproducibility in CI environments. His work included enhancing code quality through linting and removing obsolete code, as well as strengthening test governance. This contribution deepened SymPy’s interoperability with PyTorch, supporting more robust and automated ML-oriented development pipelines.

March 2025 performance summary focusing on delivering PyTorch support in SymPy and strengthening test/packaging infrastructure to accelerate ML-oriented workflows.
March 2025 performance summary focusing on delivering PyTorch support in SymPy and strengthening test/packaging infrastructure to accelerate ML-oriented workflows.
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