How can we tune network architecture hyperparameters like number of filters, filter size etc. using Bayesian Optimization? Is Bayesian Optimization only for training options?

how to tune hyperparameters of network architecture in a convolutional neural network?

which hyperparameters can be tuned using bayesian optimization and experiment manager?