tf19_saver.py

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import tensorflow as tf
import numpy as np

## Save to file
# remember to define the same dtype and shape when restore
##W = tf.Variable([[1,2,3],[3,4,5]], dtype=tf.float32, name='weights')
##b = tf.Variable([[1,2,3]], dtype=tf.float32, name='biases')
##
##init= tf.initialize_all_variables()
##
##saver = tf.train.Saver()
##
##with tf.Session() as sess:
##    sess.run(init)
##    save_path = saver.save(sess, "my_net/save_net.ckpt")
##    print("Save to path: ", save_path)
##

################################################
# restore variables
# redefine the same shape and same type for your variables
W = tf.Variable(np.arange(6).reshape((2, 3)), dtype=tf.float32, name="weights")
b = tf.Variable(np.arange(3).reshape((1, 3)), dtype=tf.float32, name="biases")

# not need init step

saver = tf.train.Saver()
with tf.Session() as sess:
    saver.restore(sess, "my_net/save_net.ckpt")
    print("weights:", sess.run(W))
    print("biases:", sess.run(b))