Einsum in 40 Lines of Python

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • einops

    Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

  • See also https://github.com/arogozhnikov/einops

    Having used these (mostly translating code that used them) I see the power and benefit. I also find it takes a lot of mentally energy to get my head around them and makes readability harder.

  • ten

    A statically typed tensor programming language for defining AI models. (by lukehoban)

  • I played around with the idea of a language motivated by this same thought process last year: https://github.com/lukehoban/ten.

    > Ten has the following features:

  • Scout Monitoring

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  • TensorOperations.jl

    Julia package for tensor contractions and related operations

  • array

    C++ multidimensional arrays in the spirit of the STL

  • I wrote a library in C++ (I know, probably a non-starter for most reading this) that I think does most of what you want, as well as some other requests in this thread (generalized to more than just multiply-add): https://github.com/dsharlet/array?tab=readme-ov-file#einstei....

    A matrix multiply written with this looks like this:

        enum { i = 2, j = 0, k = 1 };

  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

  • PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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