What skills are necessary to understand/be able to make meaningful contributions to PyTorch?

This page summarizes the projects mentioned and recommended in the original post on /r/pytorch

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  • torcheval

    A library that contains a rich collection of performant PyTorch model metrics, a simple interface to create new metrics, a toolkit to facilitate metric computation in distributed training and tools for PyTorch model evaluations.

  • Shameless plug, my team works on torcheval and torchtnt. Neither of them are core pytorch, but if you're looking to help build out tooling for metric evaluation or training frameworks, both libraries are pretty new with very low hanging fruit.

  • tnt

    A lightweight library for PyTorch training tools and utilities (by pytorch)

  • Shameless plug, my team works on torcheval and torchtnt. Neither of them are core pytorch, but if you're looking to help build out tooling for metric evaluation or training frameworks, both libraries are pretty new with very low hanging fruit.

  • Scout Monitoring

    Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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