uv-metrics is a Python library that makes it easy to instrument your machine learning workflows, report those metrics to a variety of storage backends, and analyze those metrics in a notebook or script.

UV is designed to work in or out of a Dockerized environment. It was designed alongside Caliban, and interacts nicely with Caliban's job history management features to make metrics easier than ever.

Install UV Metrics via pip:

pip install uv-metrics

Full documentation for UV lives at Read The Docs.

This is a research project, not an official Google product. Expect bugs and sharp edges. Please help by trying out UV, reporting bugs, and letting us know what you think!

If UV Metrics helps you in your research, pleae consider citing the repository:

@software{uv2020github,
  author = {Sam Ritchie},
  title = {{UV Metrics}: Metric reporting and experiment management for ML workflows.},
  url = {http://github.com/google/uv-metrics},
  version = {0.1.0},
  year = {2020},
}

In the above bibtex entry, names are in alphabetical order, the version number is intended to be that of the latest tag on github, and the year corresponds to the project's open-source release.

Copyright 2020 Google LLC.

Licensed under the Apache License, Version 2.0.