TensorFLow用Saver保存和恢复变量


            本文为大家分享了TensorFLow用Saver保存和恢复变量的具体代码，供大家参考，具体内容如下

建立文件tensor_save.py, 保存变量v1,v2的tensor到checkpoint files中，名称分别设置为v3,v4。





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)





建立文件tensor_restror.py, 将checkpoint files中名称分别为v3,v4的tensor分别恢复到变量v3,v4中。 







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, launch the model, 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))







以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持中文源码网。