举例说明函数tf.train.exponential_decay用法

import tensorflow as tf 
import matplotlib.pyplot as plt 
learning_rate = 0.1  
decay_rate = 0.99 
global_steps = 1000  
decay_steps = 100  
global_ = tf.placeholder(tf.int32)
c = tf.train.exponential_decay(learning_rate, global_, decay_steps, decay_rate, staircase=True)  
d = tf.train.exponential_decay(learning_rate, global_, decay_steps, decay_rate, staircase=False)  
T_C = []  
T_D = []  
with tf.Session() as sess:  
    sess.run(tf.global_variables_initializer())
    for i in range(global_steps):  
        T_c = sess.run(c,feed_dict={global_: i})  
        T_C.append(T_c)  
        T_d = sess.run(d,feed_dict={global_: i})  
        T_D.append(T_d)  

plt.figure(1) 
plt.plot(range(global_steps), T_D, 'r-')  
plt.plot(range(global_steps), T_C, 'b-')  
plt.show()  

参考：http://blog.youkuaiyun.com/uestc_c2_403/article/details/72356448