import tensorflow as tf
import numpy as np
##save to file
#rember 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.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)
#resotre 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))