x = tf.Variable(0.0)
#返回一个op,表示给变量x加1的操作
x_plus_1 = tf.assign_add(x, 1)
#control_dependencies的意义是,在执行with包含的内容(在这里就是 y = x)前
#先执行control_dependencies中的内容(在这里就是 x_plus_1)
with tf.control_dependencies([x_plus_1]):
y = x
init = tf.initialize_all_variables()
with tf.Session() as session:
init.run()
for i in xrange(5):
print(y.eval())
https://www.cnblogs.com/lovychen/p/8617524.html