OptunAPI is a simple API designed for Machine Learning applications that allows to distribute an automatic hyperparameters optimization over different machines through HTTP requests. Each set of hyperparameters can be studied independently since the minima research does’t require any gradients computation, but instead is performed through a Bayesian optimization based on Optuna. The machine running Optuna manages centrally the optimization studies – the so-called “Optuna-server” – providing sets of hyperparameters and assessing them by the scores evaluated and sent back by the single computing instance, named “Trainer-client”. The HTTP requests underlying such client-server system are powered by FastAPI.

A simple sketch representing how OptunAPI works.