This is a great development for both new and experienced users. Most importantly, it seems to be an effort to introduce a canonical way to build a given network in Tensorflow, as opposed to the previous era where any given TF repo might implement the same network in one of several completely different ways (tf.contrib.slim, tf.layers, etc). Hopefully, defining a standard way to build models will also help accelerate the standardization of train/test scripts and data pipelines, putting to rest the era of models being deeply infected with the execution structure built around them.

Overall, it looks like Pytorch is forcing TF devs to focus more on users and usability, and I'm excited to see how they continue to spur each other's growth.