TensorFLow用Saver保存和恢复变量

import tensorflow as tf

# Create some variables.
v1 = tf.Variable(3,name="v1")
v2 = tf.Variable(4,name="v2")

# Create model
y=tf.add(v1,v2)

# Add an op to initialize the variables.
init_op = tf.initialize_all_variables()

# Add ops to save and restore all the variables.
saver = tf.train.Saver({'v3':v1,'v4':v2})

# Later,launch the model,initialize the variables,do some work,save the
# variables to disk.
with tf.Session() as sess:
 sess.run(init_op)
 print("v1 = ",v1.eval())
 print("v2 = ",v2.eval())
 # Save the variables to disk.
 save_path = saver.save(sess,"f:/tmp/model.ckpt")
 print ("Model saved in file: ",save_path)

import tensorflow as tf

# Create some variables.
v3 = tf.Variable(0,name="v3")
v4 = tf.Variable(0,name="v4")

# Create model
y=tf.mul(v3,v4)

# Add ops to save and restore all the variables.
saver = tf.train.Saver()

# Later,use the saver to restore variables from disk,and
# do some work with the model.
with tf.Session() as sess:
 # Restore variables from disk.
 saver.restore(sess,"f:/tmp/model.ckpt")
 print ("Model restored.")
 print ("v3 = ",v3.eval())
 print ("v4 = ",v4.eval())
 print ("y = ",sess.run(y))