We have not yet released examples of interfaces with Pytorch. Maybe with moderate number of hyperparameters the benefit compared to random search will be moderate, whereas it will be very significant with high number of hyperparameters. It also depends on how parallel you are. In all cases we have a wide range of algorithms with a common interface, so that you can compare.

We also use it for direct training of the weights of a network in reinforcement learning, not only hyperparameters.