The idea of this library is to show the inner workings of the GANs as they’re publicized in the papers, but I will definitely make some examples with TFGANs in the future for broader exposition. ;)
I've read a little bit about it. I think it would be a good idea since we don't need to run the subgraphs on parallel or something like that, therefore eliminating the need for a TF session per se.
I'll be helping Diego with some new models, it'd be awesome if you join :)
https://research.googleblog.com/2017/12/tfgan-lightweight-li...
https://github.com/tensorflow/tensorflow/tree/master/tensorf...