convsave.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.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 dtype 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)