Catgrad: A Category-Theoretic Deep Learning Compiler
2025-02-05
Catgrad is a deep learning framework that leverages category theory to statically compile models into their forward and backward passes. This allows your training loop to run without needing any deep learning framework (not even catgrad itself!). Built upon research papers exploring categorical approaches to deep learning, it enables features like data-parallel algorithms and differentiable polynomial circuits. Installation is straightforward via `pip install catgrad`.
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