tensorflow_study9_savemodel.py

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.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 adn 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')

# no 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))