Tensorflow学习： 保存变量和网络

import tensorflow as tf
import numpy as np
#
## Save to file
# remerber 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, "logs/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')

saver = tf.train.Saver()

with tf.Session() as sess:
saver.restore(sess, "logs/save_net.ckpt")
print("Weights: ", sess.run(W))
print("baises: ", sess.run(b))