DeepHyper is first and foremost a hyperparameter optimization (HPO) library. By leveraging this core HPO functionality, DeepHyper also provides neural architecture search, multi-fidelity and ensemble capabilities. With DeepHyper, users can easily perform these tasks on a single machine or distributed across multiple machines, making it ideal for use in a variety of environments.

The project is organized across different repositories:

• deephyper: Main Python package.
• documentation: Documentation website.
• benchmark: Set of benchmarks to evaluate the performance.