Suppose I have a somewhat complicated hyper parameter distribution I’d like to sample:
For example, I have a hyperparameter called HP1 controlling normalization applied my dataset. If I sample HP1 ← maximum-eigenvalue-norm, then maybe I have another hyperparameter I must sample; in this case that could be how to compute maximum eigenvalue which could be in the set {fancy-eigenvalue-computation, torch-built-in-symeig}.
But suppose if normalization technique was sampled as HP1 ← Frobenius-norm, then I have no other hyper parameters to sample.
Optuna handles this nicely, and I was hoping W&B’s had a similar way of auto-magically handling it.