As it is mentioned on the github page, the project was inspired from keras and other great projects, but many decisions did not completely fit with the way keras does things. There will be support for keras models in the future, but currently we are trying finish the work on the web api, the web ui and the cli.

> but many decisions did not completely fit with the way keras does things

That's interesting. Could you expand on this some more?

Sure, one of the reasons why we couldn't base the code on Keras at the time when we start working on the project was the integration of keras into the Estimator api, meaning that we couldn't have used the distributed training that was offered by the tensorflow team.

Ok, sounds like a good reason. But how is that situation now? Did the Keras team remove that limitation in the meantime?

I understand your concerns, we had the same reactions from some of our friends, and I can assure you that the integration is planned, and any redundancy, duplication, or patches that we have right now for some tf code will be removed.

thank you for taking the time to have a look at the project, and I am very happy that we are receiving such a constructive criticism.

It was always possible to train Keras models in a distributed setting (I was doing it in late 2015). And there's built-in, one-line integration with the Estimator API coming in the next version of TensorFlow.