Skip to main content

Metric logger for ML projects.

Project description

DVCLive

GHA Tests Codecov Donate

PyPI

DVCLive is an open-source library for monitoring the progress of metrics during training of machine learning models. It’s built with Git and MLOps principles in mind:

  1. Codification of data. Tracked metrics are stored in readable text files that can be versioned by Git or other version control tools.

  2. Distributed. No services or servers are required. Metrics are stored in a Git repository as text files, or pointers to files in DVC storage.

  3. GitOps API. Plots are generated through DVC using Git commit SHAs or branch names, e.g.: dvc plots diff --target logs master.

https://dvc.org/static/cdc4ec4dabed1d7de6b8606667ebfc83/9da93/dvclive-diff-html.png
  1. Automation. DVCLive metrics are easy to use by any automation, DevOps, or MLOps tool such as CI/CD (including CML), custom scripts, or ML platforms.

DVCLive integrates seamlessly with DVC; the logs/summaries it produces can be fed as dvc plots/dvc metrics.

However, DVC is not required to work with dvclive logs/summaries, and since they’re saved as easily parsable .tsv/.json files, you can use your preferred visualization method.

Quick Start

Please read the Usage guide for a detailed version.

DVCLive is a Python library. The interface consists of three main methods:

  1. dvclive.init()

  2. dvclive.log()

  3. dvclive.next_step()

If you are ussing a ML training framework, check the existing ML Frameworks page.

Installation

pip (PyPI)

PyPI

pip install dvclive

Depending on the ML framework you plan to use to train your model, you might need to specify one of the optional dependencies: mmcv, tf, xgb. Or all to include them all. The command should look like this: pip install dvclive[tf] (in this case TensorFlow and it’s dependencies will be installed automatically).

To install the development version, run:

pip install git+git://github.com/iterative/dvclive

Call to collaboration

Today only Python is supported (while DVC is language agnostic), along with the following ML frameworks:

The DVCLive team is happy to extend the functionality as needed. Please create an issue or check the existing ones to start a discussion!

Project details


Release history Release notifications | RSS feed

This version

0.4.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dvclive-0.4.0.tar.gz (17.8 kB view hashes)

Uploaded Source

Built Distribution

dvclive-0.4.0-py2.py3-none-any.whl (25.2 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page