A framework for elegantly configuring complex applications.

Check the website for more information,
or click the thumbnail below for a one-minute video introduction to Hydra.

Hydra 1.3 is the stable version of Hydra.

• Documentation
• Installation : pip install hydra-core --upgrade

See the NEWS.md file for a summary of recent changes to Hydra.

Hydra is licensed under MIT License.

• hydra-zen: Pythonic utilities for working with Hydra. Dynamic config generation capabilities, enhanced config store features, a Python API for launching Hydra jobs, and more.
• lightning-hydra-template: user-friendly template combining Hydra with Pytorch-Lightning for ML experimentation.
• hydra-torch: configen-generated configuration classes enabling type-safe PyTorch configuration for Hydra apps.
• NVIDIA's DeepLearningExamples repository contains a Hydra Launcher plugin, the distributed_launcher, which makes use of the pytorch distributed.launch API.

• Github Discussions
• StackOverflow
• Twitter

Check out the Meta AI blog post to learn about how Hydra fits into Meta's efforts to reengineer deep learning platforms for interoperability.

If you use Hydra in your research please use the following BibTeX entry:

@Misc{Yadan2019Hydra,
  author =       {Omry Yadan},
  title =        {Hydra - A framework for elegantly configuring complex applications},
  howpublished = {Github},
  year =         {2019},
  url =          {https://github.com/facebookresearch/hydra}
}