During February 2025, this developer enhanced the tenstorrent/tt-metal repository by introducing average pooling support to the existing pooling program factory. They extended the C++ codebase to generalize pooling logic, allowing both max and avg_pool2d operations to be handled within a unified framework. The implementation included comprehensive Python-based tests to verify correct behavior across pooling modes, ensuring model inference flexibility and compatibility with deep learning workflows. By reusing and adapting the existing infrastructure, the work enabled broader model support without duplicating code. No major bugs were reported, reflecting a focused and well-tested approach to feature development in machine learning systems.