吴裕雄 PYTHON 神经网络——TENSORFLOW 滑动平均模型

import tensorflow as tf

v1 = tf.Variable(0, dtype=tf.float32)
step = tf.Variable(0, trainable=False)
ema = tf.train.ExponentialMovingAverage(0.99, step)
maintain_averages_op = ema.apply([v1]) 

with tf.Session() as sess:

    # 初始化
    init_op = tf.global_variables_initializer()
    sess.run(init_op)
    print(sess.run([v1, ema.average(v1)]))

    # 更新变量v1的取值
    sess.run(tf.assign(v1, 5))
    sess.run(maintain_averages_op)
    print(sess.run([v1, ema.average(v1)]) )

    # 更新step和v1的取值
    sess.run(tf.assign(step, 10000))
    sess.run(tf.assign(v1, 10))
    sess.run(maintain_averages_op)
    print(sess.run([v1, ema.average(v1)]))       

    # 更新一次v1的滑动平均值
    sess.run(maintain_averages_op)
    print(sess.run([v1, ema.average(v1)]))