Convert Keras model to TensorFlow protobuf

Question

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 t

Answer 1

Save your keras model as an HDF5 file.

You can then do the conversion with the following code:

from keras import backend as K
from tensorflow.python.framework import graph_util
from tensorflow.python.framework import graph_io

weight_file_path = 'path to your keras model'
net_model = load_model(weight_file_path)
sess = K.get_session()

constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph.as_graph_def(), 'name of the output tensor')
graph_io.write_graph(constant_graph, 'output_folder_path', 'output.pb', as_text=False)
print('saved the constant graph (ready for inference) at: ', osp.join('output_folder_path', 'output.pb'))

Here is my sample code which handles multiple input and multiple output cases: https://github.com/amir-abdi/keras_to_tensorflow