TensorFlow手把手入门之 — TensorFlow保存还原模型的正确方式，Saver的save和restore方法，亲测可用

许多TensorFlow初学者想把自己训练的模型保存，并且还原继续训练或者用作测试。但是TensorFlow官网的介绍太不实用，网上的资料又不确定哪个是正确可行的。

今天David 9 就来带大家手把手入门亲测可用的TensorFlow保存还原模型的正确方式，使用的是网上最多的Saver的save和restore方法， 并且把关键点为大家指出。

今天介绍最为可行直接的方式来自这篇Stackoverflow：https://stackoverflow.com/questions/33759623/tensorflow-how-to-save-restore-a-model 亲测可用：

保存模型：

import tensorflow as tf

#Prepare to feed input, i.e. feed_dict and placeholders
w1 = tf.placeholder("float", name="w1")
w2 = tf.placeholder("float", name="w2")
b1= tf.Variable(2.0,name="bias")
feed_dict ={w1:4,w2:8}

#Define a test operation that we will restore
w3 = tf.add(w1,w2)
w4 = tf.multiply(w3,b1,name="op_to_restore")
sess = tf.Session()
sess.run(tf.global_variables_initializer())

#Create a saver object which will save all the variables
saver = tf.train.Saver()

#Run the operation by feeding input
print sess.run(w4,feed_dict)
#Prints 24 which is sum of (w1+w2)*b1 

#Now, save the graph
saver.save(sess, 'my_test_model',global_step=1000)

必须强调的是：这里4,5,6,11行中的name=’w1′, name=’w2′,  name=’bias’, name=’op_to_restore’ 千万不能省略，这是恢复还原模型的关键。

还原模型：

import tensorflow as tf

sess=tf.Session()    
#First let's load meta graph and restore weights
saver = tf.train.import_meta_graph('my_test_model-1000.meta')
saver.restore(sess,tf.train.latest_checkpoint('./'))


# Access saved Variables directly
print(sess.run('bias:0'))
# This will print 2, which is the value of bias that we saved


# Now, let's access and create placeholders variables and
# create feed-dict to feed new data

graph = tf.get_default_graph()
w1 = graph.get_tensor_by_name("w1:0")
w2 = graph.get_tensor_by_name("w2:0")
feed_dict ={w1:13.0,w2:17.0}

#Now, access the op that you want to run. 
op_to_restore = graph.get_tensor_by_name("op_to_restore:0")

print sess.run(op_to_restore,feed_dict)
#This will print 60 which is calculated

还原当然是用restore方法，这里的18,19,23行就是刚才的name关键字指定的Tensor变量，必须找对才能进行还原恢复。

其他的关键在代码和注释中可以一眼看出， 这里不加赘述了。

 

参考文献：

  1. https://stackoverflow.com/questions/33759623/tensorflow-how-to-save-restore-a-model
  2. https://nathanbrixius.wordpress.com/2016/05/24/checkpointing-and-reusing-tensorflow-models/
  3. https://stackoverflow.com/questions/42685994/how-to-get-a-tensorflow-op-by-name
  4. http://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/
  5. https://www.tensorflow.org/versions/r0.11/api_docs/python/state_ops/saving_and_restoring_variables

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