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It looks like they are using both TensorFlow and Theano. Is there a reason to use both?

The VAE code and the semi-supervised part of the GAN code build on code that was developed about half a year ago, when Tensorflow was less developed and was lacking in speed and functionality compared to Theano. It has since caught up and most new projects at OpenAI are now done using Tensorflow, which is what we used for the newer additions.

Could you mention a bit about why you're using Tensorflow?

I'm glad you are since I'm using it myself, but I haven't used any other frameworks so I'm wondering if I should expect more people to head in this direction, or spend time learning others.

There are currently many excellent frameworks to choose from: TensorFlow, Theano, Torch, MXNet are all great. The comparative advantage of TensorFlow is mostly its support in the community (e.g. most stars on GitHub, most new projects being developed, etc).

The community around Tensorflow is great (lots of people that try to recreate results from new papers using TF), but if you're worried about putting all your eggs in one basket (or want to be a higher level up) you should checkout Keras if you haven't yet. It lets you write generic nets that can run on Theano or TF.

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