Skip to main content

Metric logger for ML projects.

Project description

dvclive is an open-source library for monitoring machine learning model performance.

dvclive aims to provide the user with simple python interface what will allow the

user to log the model metrics as the training progresses.

The interface consists of three main methods:

  1. dvclive.init(path) - initializes dvclive logger. The metrics will be saved under path.

  2. dvclive.log(metric, value, step) - logs the metric value. The value and step will be appended to path/{metric}.tsv file. The step value is optional.

  3. dvclive.next_step() - signals dvclive that current step has ended. Executed automatically if same metric is logged again.

Project details


Release history Release notifications | RSS feed

This version

0.0.1

Download files

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

Source Distribution

dvclive-0.0.1.tar.gz (7.4 kB view hashes)

Uploaded Source

Built Distribution

dvclive-0.0.1-py2.py3-none-any.whl (13.6 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