Good to hear Theano has come back to life, it was my first deep learning library :). These days I do PyTorch, and while I really appreciate its debuggability and flexibility, I definitely can see in retrospect some of the advantages of Theano's declarative approach.

In that regard, I am curious about why Tensorflow didn't work out. I understand Tensorflow version 1 implements a declarative mode that I guess is in many ways similar to Theano's. I'm assuming v2 still supports that mode, on top of the new eager mode -- is that the case? If so, was there some aspect of its implementation that made it unsuitable for PyMC?