def restore_weights()

in demo.py [0:0]

• 8 lines of code
• 6 McCabe index (conditional complexity)

def restore_weights(sess,opt):
	var_list = tf.trainable_variables()
	g_list = tf.global_variables()

	# add batch normalization params into trainable variables 
	bn_moving_vars = [g for g in g_list if 'moving_mean' in g.name]
	bn_moving_vars += [g for g in g_list if 'moving_variance' in g.name]
	var_list +=bn_moving_vars

	# create saver to save and restore weights
	saver = tf.train.Saver(var_list = var_list)
	saver.restore(sess,opt.pretrain_weights)