采用TensorFlow支持通过tf.Graph函数来生成新的向量图,代码如下:
import tensorflow as tf g1 = tf.Graph() with g1.as_default(): v = tf.get_variable( "v",initializer=tf.zeros_initializer(shape = [1])) g2 = tf.Graph() with g2.as_default(): v = tf.get_variable( "v",initializer=tf.ones_initializer(shape = [1])) with tf.Session(graph=g1) as sess: tf.initialize_all_variables().run() with tf.variable_scope("",reuse=True): print(sess.run(tf.get_variable("v"))) with tf.Session(graph=g2) as sess: tf.initialize_all_variables().run() with tf.variable_scope("",reuse=True): print(sess.run(tf.get_variable("v")))
执行后发生如下错误:
解决办法:因为上述代码写法是TensorFlow旧版本的写法,将Line6 和Line10 改如下如下可以实现代码的正常运行:
v = tf.get_variable("v",initializer=tf.zeros_initializer()(shape = [1]))
v = tf.get_variable( "v",initializer=tf.ones_initializer()(shape = [1]))
输出结果如下图:
明显有一个更新提示,表示该初始化的语句也需要进行更新:
tf.initialize_all_variables().run() 变成 tf.global_variables_initializer().run()
最后输出结果:
源于博客:https://blog.csdn.net/li_haiyu/article/category/7625657