def compare_inception_v3(src1, src2):
graph = tf.Graph()
with graph.as_default():
with tf.Session() as sess:
network = inception_v3(sess)
network.restore_graph(src1)
weights = network.get_all_weights()
network.restore_graph(src2)
total_weight, equal_weight = network.comp_graph(weights)
print ('Total weight : %d / Equal weight : %d' % \
(total_weight, equal_weight))
def generate_pretrained_prunable_inception_v3(src, dst):
graph = tf.Graph()
with graph.as_default():
with tf.Session() as sess:
network = inception_v3(sess)
network.restore_graph(src)
weights = network.get_all_weights()
tf.reset_default_graph()
graph = tf.Graph()
with graph.as_default():
with tf.Session() as sess:
network = prunable_inception_v3(sess)
network.replace_graph(weights)
network.save_graph(dst)
def print_inception_v3(src):
with tf.Session() as sess:
network = inception_v3(sess)
network.restore_graph(src)
network.print_all_weights()
def generate_pretrained_inception_v3(src, dst):
with tf.Session() as sess:
network = inception_v3(sess)
network.restore_graph(src)
network.save_graph(dst)
def generate_zero_inception_v3(dst):
with tf.Session() as sess:
network = inception_v3(sess)
network.reset_all_weights()
network.save_graph(dst)