This repository contains common functionality for writing ML training loops. The goal is to make trainings loops short and readable (but moving common tasks to small libraries) without removing the flexibility required for research.
To get started, check out this Colab:
https://colab.research.google.com/github/google/CommonLoopUtils/blob/main/clu_synopsis.ipynb
If you're looking for usage examples, see:
https://github.com/google/flax/tree/main/examples
You can also find answers to common questions about CLU on Flax Github discussions page:
https://github.com/google/flax/discussions
Note: As this point we are not accepting contributions. Please fork the repository if you want to extend the libraries for your use case.
FAQs
Set of libraries for ML training loops in JAX.
We found that clu demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Fluent Assertions is facing backlash after dropping the Apache license for a commercial model, leaving users blindsided and questioning contributor rights.
Research
Security News
Socket researchers uncover the risks of a malicious Python package targeting Discord developers.
Security News
The UK is proposing a bold ban on ransomware payments by public entities to disrupt cybercrime, protect critical services, and lead global cybersecurity efforts.
