Importing Tensorflow Session Bundle in Python
Question: How do you import from inside Python a Tensorflow session bundle? The docs
explain [exporting from
Python](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/session_bundle#exporting-
python-code) and [importing in
C++](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/session_bundle#importing-
c-code).

UPDATE: I found the following:

  1. [`load_session_bundle_from_path`](https://github.com/tensorflow/tensorflow/blob/c856366b739850a9f4b0bf1469de7f052619042b/tensorflow/contrib/session_bundle/session_bundle.py#L35)
  2. [`python.saved_model.loader.load`](https://github.com/tensorflow/tensorflow/blob/c856366b739850a9f4b0bf1469de7f052619042b/tensorflow/python/saved_model/loader.py#L119)


Answer: SessionBundle consists of a checkpoint and a MetaGraph definition that's
needed for serving (see
[here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/session_bundle)).
Since TensorFlow Serving is in C++, I don't think you will find any Python
examples).

However, if you are using Python, you don't actually need this MetaGraph
definition, you can just start a new session and restore from the checkpoint
file, and subsequently do the inferences from this new session. You can find
some good examples
[here](http://stackoverflow.com/questions/38935428/tensorflow-rest-frontend-
but-not-tensorflow-serving).

