It has to be consistent and there has to be one way to do it.
I personally have a 10 message thread with Google cloud support on exporting a Cloud trained model to tensorflow and nobody could figure it out [Case #13619720].
In fact if you dig up the case, then even official support told me that savedmodel needs some freezing using bazel otherwise it doesn't work.
The github page and stackoverflow are full of these. If you can, please take the message to the other side :(
I don't think the cloud guys (where training will happen in distributed mode) talk to the android guys (where models will be used after quantization). There is a huge serialization problem that all of us are currently struggling with.
I really pray the tensorflow teams give it due importance.
1. We don't know what to use and its very confusing. For example, now there is https://stackoverflow.com/questions/42216208/should-tensorfl.... Will freeze_graph become canonical and we forget about SavedModel? And everything else deprecated? It should be part of the core API and workable on CloudML, where we don't have a lot of control on running scripts and certainly not Bazel builds.
2. Android/ios story. Now you have the Pixel Visual Core as well... Please make it seamless all the way to Android or Ios or raspberry pi (whatever you guys support).