new_contents: # View more python tutorials on my Youtube and Youku channel!!!
  
  # Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
  # Youku video tutorial: http://i.youku.com/pythontutorial
  
  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))
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
subject: create tf19