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.
Research
Security News
Socket’s threat research team has detected six malicious npm packages typosquatting popular libraries to insert SSH backdoors.
Security News
MITRE's 2024 CWE Top 25 highlights critical software vulnerabilities like XSS, SQL Injection, and CSRF, reflecting shifts due to a refined ranking methodology.
Security News
In this segment of the Risky Business podcast, Feross Aboukhadijeh and Patrick Gray discuss the challenges of tracking malware discovered in open source softare.
