import tensorflow as tf
import numpy as np
#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.global_variables_initializer()
#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))