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TensorFlow-模型的保存和调用(ckpt方式)
硬件:NVIDIA-GTX1080
软件:Windows7、python3.6.5、tensorflow-gpu-1.4.0
一、基础知识
1、checkpoint:模型文本信息
2、meta:模型graph,调用时可重载入
3、index、data:模型数据
二、代码展示
1、保存模型
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()
#define saver
saver = tf.train.Saver()
with tf.Session() as sess:
sess.run(init)
#save ckpt
save_path = saver.save(sess, "my_net/save_net.ckpt")
print("Save to path: ", save_path)
2、调用模型
import tensorflow as tf
import numpy as np
with tf.Session() as sess:
# restore graph
saver = tf.train.import_meta_graph('my_net/save_net.ckpt.meta')
#restore ckpt
saver.restore(sess, "my_net/save_net.ckpt")
# check variable W and b, like weight or bias
print("weights:", sess.run('weights:0'))
print("biases:", sess.run('biases:0'))
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