Automated hyperparameter optimization

[suhacker1]

Is your feature request related to a problem? Please describe.
Presently, users have to manually pick different hyperparameters for training a substitute model and other phases of each attack. However, constructing an effective attack often requires these hyperparameters to be optimized.

Describe the solution you'd like.
Optuna is a commonly used library to facilitate automated hyperparameter optimized. Different techniques should be tested in order to determine what the best optimization strategy is for PrivacyRaven.

Describe alternatives you've considered.
Other hyperparameter libraries can be used.

Detail any additional context.
The PyTorch Lightning parameters already contained within PrivacyRaven can be changed if needed. Additionally, the hyperparameters are stored within a dictionary, but can be move to an enum or other suitable solution.