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.csdn.net/uestc_c2_403/article/details/72356448