I’m pretty new to the whole idea of SVI. So I’m just wondering what happens if I define a neural network with dropout in it, and then put priors on the weights and use SVI to approximate the posterior. In the prediction process, is dropout still on? Because in normal neural nets, the network is set to .eval() when making predictions. But I don’t see this in the whole SVI setting.