This question was made before the documentation for save and restore was available. For now I would consider this question deprecated and say people to rely on the official
As described by Hamed, the right way to do it on tensorflow is
saver=tf.train.Saver()
save_path='checkpoints/'
-----> while training you can store using
saver.save(sess=session,save_path=save_path)
-----> and restore
saver.restore(sess=session,save_path=save_path)
this will load the model where you last saved it and will the training(if you want) from there only.