I think Keras is a real deal framework. It provides a higher-level API than most other frameworks, but it has pretty sweet portability of models across frameworks and platforms and most research papers are implementable in Keras without too much trouble.
In my opinion, the real deal with Pytorch or Chainer, there are similar than numpy API. So the learning curve is flat. The NN construction part and gradiant part are specific but all the glue is regular python unlike Keras, tensorflow ...
