TensorFlow Android App Debugging (3) -- Keras to TensorFlow Model Conversion

Deep learning model can be programmed using different libraries. Among them, Keras is one of the most easy to use. However, network model generated using Keras can''t be directly applied to Android app. First it needs to be converted to TensorFlow. A conversion tool is provided here to automatically convert Keras model to TensorFlow. The instruction of this tool is straightforward. It converts .h5 (Keras model) to .pb (TensorFlow model).

    python keras_to_tensorflow.py 

        --input_model="path/to/keras/model.h5" 

        --output_model="path/to/save/model.pb"

For verification purpose, we can use tool named Tensorboard to visualize the generated model. As the first step, the model will be read into a folder by script read_pb_model.py. The default folder name is tf_summary.

python read_pb_model.py model.pb

Then tensorboard will convert the folder's content to a graph, and display it in a webpage such as http://nan-System-Product-Name:6006. Below is an instruction of tensorboard 

tensorboard --logdir ./tf_summary

An example of generated graph is shown below. The graph displays the network topology. It also shows the name of the node. It is important to know the names. In Android app, when one needs to access certain part of the network model, he has to use the name as reference.