70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
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#!/usr/bin/env python3
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#
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# Attribution: This script was adapted from https://github.com/amir-abdi/keras_to_tensorflow
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#
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# Copyright (c) 2017 Mycroft AI Inc.
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import sys
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sys.path += ['.']
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import argparse
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import os
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from os.path import split, isfile
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from shutil import copyfile
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def convert(model_path, out_file):
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"""
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Converts an HD5F file from Keras to a .pb for use with TensorFlow
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Args:
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model_path (str): location of Keras model
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out_file (str): location to write protobuf
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"""
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print('Converting', model_path, 'to', out_file, '...')
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import tensorflow as tf
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from keras.models import load_model
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from keras import backend as K
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out_dir, filename = split(out_file)
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out_dir = out_dir or '.'
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os.makedirs(out_dir, exist_ok=True)
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K.set_learning_phase(0)
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model = load_model(model_path)
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out_name = 'net_output'
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tf.identity(model.output, name=out_name)
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print('Output node name:', out_name)
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print('Output folder:', out_dir)
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sess = K.get_session()
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# Write the graph in human readable
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tf.train.write_graph(sess.graph.as_graph_def(), out_dir, filename + 'txt', as_text=True)
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print('Saved readable graph to:', filename + 'txt')
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# Write the graph in binary .pb file
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from tensorflow.python.framework import graph_util
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from tensorflow.python.framework import graph_io
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cgraph = graph_util.convert_variables_to_constants(sess, sess.graph.as_graph_def(), [out_name])
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graph_io.write_graph(cgraph, out_dir, filename, as_text=False)
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if isfile(model_path + '.params'):
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copyfile(model_path + '.params', out_file + '.params')
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print('Saved graph to:', filename)
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del sess
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Convert keyword model from Keras to TensorFlow')
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parser.add_argument('--model','-m', default='keyword.net', help='Input Keras model', type=argparse.FileType())
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parser.add_argument('--out', '-o', default='keyword.pb', help='Output TensorFlow protobuf')
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args = parser.parse_args()
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convert(args.model.name, args.out)
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