tensorflow-6

tf.train.ExponentialMovingAverage使用举例

import tensorflow as tf;  
import numpy as np;  
import matplotlib.pyplot as plt;  
  
v1 = tf.Variable(0, dtype=tf.float32)  
step = tf.Variable(tf.constant(0))  
  
ema = tf.train.ExponentialMovingAverage(0.99, step)  
maintain_average = ema.apply([v1])  
  
with tf.Session() as sess:  
    init = tf.initialize_all_variables()  
    sess.run(init)  
  
    print sess.run([v1, ema.average(v1)]) #初始的值都为0  
  
    sess.run(tf.assign(v1, 5)) #把v1变为5  
    sess.run(maintain_average)  
    print sess.run([v1, ema.average(v1)]) # decay=min(0.99, 1/10)=0.1, v1=0.1*0+0.9*5=4.5  
  
    sess.run(tf.assign(step, 10000)) # steps=10000  
    sess.run(tf.assign(v1, 10)) # v1=10  
    sess.run(maintain_average)  
    print sess.run([v1, ema.average(v1)]) # decay=min(0.99,(1+10000)/(10+10000))=0.99, v1=0.99*4.5+0.01*10=4.555  
  
    sess.run(maintain_average)  
    print sess.run([v1, ema.average(v1)])