Distributed Bayesian Deep Learning using Variational Inference

I’m about to embark on a project doing distributed variational inference on (Bayesian) deep learning. What are the existing resources for Bayesian deep learning in pytorch – or more broadly in python at the moment (I’m only aware of ZhuSuan, https://github.com/thu-ml/zhusuan, which is designed on top of tensorflow)?

Have a look at BoTorch.

Thanks for the reply.
It looks to me that BoTorch primarily supports Bayesian Optimization on (frequentist) neural networks. Is it going to be expanded to include Bayesian inference for deep models?