labml

labml is an experiment-tracking and monitoring toolkit aimed at machine learning practitioners who want to check on long-running training jobs, including from their phone, without staying tied to a terminal or a single workstation. It integrates with common deep learning frameworks and tracks experiment metadata alongside training metrics.

With as little as two lines of code, it can track git commit information, configuration values and hyperparameters for an experiment, alongside the usual loss and metric curves, and it works with PyTorch, PyTorch Lightning, Keras, TensorFlow and fastai based on its listed topics. A single command also monitors hardware usage on any machine. An optional self-hosted experiments server, backed by MongoDB and optionally fronted by Nginx, provides the web interface for viewing experiments remotely, including from a mobile browser.

labml is written in Python and released under the MIT license. It is installed via pip, both for the monitoring client embedded in training scripts and for the self-hosted server component, and its documentation covers the Python API, custom visualizations and configuration management in more depth.