Hipshot without having run the code:
Iirc the reparametrization trick is just to avoid taking the gradient of generating random numbers, like you do here: eps = rand(MvNormal(vec(fill(0., 32)), vec(std))). You probably need to tell Zygote to not try to differentiate that line, e.g. using @nograd.
Another issue with the model is that all those anonymous functions are not functors and therefore their parameters will not be captured by params. I’m also uncertain if Flux.Params(model) does the same thing as params(model). In either case, you need to give params all the layers with parameters you want to train. I think that `params([encoder, eH1, eH2, decoder]) should work.