Deep learning platform Atlas is now open source

This week, Dessa launched Atlas as an open source platform for developing deep learning projects. The deep learning startup Dessa was acquired by Square in February 2020.

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Let’s see what features this beta version of their deep learning platform has to offer.

Features of Atlas

Atlas has a Python SDK, CLI, GUI and scheduler on board. These aspects should help reduce the effort of managing infrastructure and increase the speed of developing deep learning models.

The deep learning platform is self-hosted and runs on either a single node, a multi-node cluster or on multi-cloud clusters. It supports job scheduling to allow collaboration, and every job is reproducible because it is recorded and tracked.

On Twitter, Dessa posted a demonstration of Atlas:

We open source, and now we hope you’ll open source Atlas:

As of today, our DL dev platform Atlas is now open source! Excited to collaborate with bright people around the world to make these tools even more helpful. Learn more here: https://t.co/OGIM5G1ZxC pic.twitter.com/LfMzJ3T0y8

— Dessa (@dessa) March 17, 2020

Integration with TensorBoard, TensorFlow’s visualization toolkit, is included. Atlas can “run any Python code with any frameworks,” as the GitHub documentation states.

Getting started

Installation guides for Atlas are available for macOS, Linux and Windows 10.

On Windows, for example, the installation should take 10 minutes. The requirements are a Docker version higher than 18.09, Python 3.6 or higher, more than 5GB of free storage and the atlas_installer.py file, which you can get here.

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See the Square blog post for further details.

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