tensorflow 只恢复部分模型参数的实例

我就废话不多说了，直接上代码吧！importtensorflowastfdefmodel_1():withtf.variable_scope("var_a"):a=tf.Var

我就废话不多说了，直接上代码吧！

import tensorflow as tf

def model_1():
 with tf.variable_scope("var_a"):
 a = tf.Variable(initial_value=[1, 2, 3], name="a")

 vars = [var for var in tf.trainable_variables() if var.name.startswith("var_a")]
 print(len(vars))
 return vars

def model_2():

 vars1 = model_1()

 with tf.variable_scope("var_b"):
 a = tf.Variable(initial_value=[1, 2, 3], name="a")

 vars2 = [var for var in tf.trainable_variables() if var.name.startswith("var")]
 print(len(vars2))
 return vars1


def pretrain_model1():
 print("-------- model 1 ------")
 vars = model_1()

 with tf.Session() as sess:
 sess.run(tf.global_variables_initializer())
 saver = tf.train.Saver()
 saver.save(sess, "./model.ckpt")

def train_model2():
 print("-------- model 2 ------")

 model1_vars = model_2()

 with tf.Session() as sess:
 sess.run(tf.global_variables_initializer())
 saver = tf.train.Saver(var_list=model1_vars)
 saver.restore(sess, "./model.ckpt")
 vars = sess.run([model1_vars])
 for var in vars:
 print(var)

step = 2
if step == 1:
 pretrain_model1()
else:
 train_model2()

以上这篇tensorflow 只恢复部分模型参数的实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持脚本之家。