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We're currently training various neural networks using Keras, which is ideal because it has a nice interface and is relatively easy to use, but we'd like to be able to apply them in our production environment.
Unfortunately the production environment is C++, so our plan is to:
Unfortunately I don't know how to access the TensorFlow saving utilities from Keras, which normally saves to HDF5 and JSON. How do I save to protobuf?
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The protobuf tools parse this text file, and generate the code to load, store, and manipulate graph definitions. If you see a standalone TensorFlow file representing a model, it's likely to contain a serialized version of one of these GraphDef objects saved out by the protobuf code.
The . pb format is the protocol buffer (protobuf) format, and in Tensorflow, this format is used to hold models. Protobufs are a general way to store data by Google that is much nicer to transport, as it compacts the data more efficiently and enforces a structure to the data.
In case you don't need to utilize a GPU in the environment you are deploying to, you could also use my library, called frugally-deep. It is available on GitHub and published under the MIT License: https://github.com/Dobiasd/frugally-deep
frugally-deep allows running forward passes on already-trained Keras models directly in C++ without the need to link against TensorFlow or any other backend.
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