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arogozhnikov/einops ★ 9616 403 APPLICATION

Einops is a Python library that provides a uniform, readable, and reliable API for tensor manipulation across multiple deep learning frameworks (NumPy, PyTorch, TensorFlow, JAX, and others). It uses Einstein-like notation (e.g., 'b c h w -> b h w c') to express axis reordering, composition, decomposition, reduction, and repetition in a single, explicit string. The library is built around a core transformation engine that parses axis patterns into a cached 'TransformRecipe', which is then applied via a backend abstraction layer. This architecture allows einops to support 10+ frameworks with minimal code duplication, while also providing framework-specific layer wrappers (Rearrange, Reduce, EinMix) for seamless integration into model definitions. The library is designed for production and research use, with a focus on reducing errors from manual view/permute/transpose operations.

RATING: 9.2/10 MAINT: active DRIFT: low
#tensor-manipulation #deep-learning #einstein-notation #framework-agnostic #python-library #machine-learning-operations #pytorch #jax #tensorflow #numpy #cupy #tensor #einops #mlx
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