学习率

来源：中国大学MOOC 曹健 《TensorFlow笔记》

 学习率：参数每次更新的幅度。

#coding:utf-8
#设损失函数 loss=(w+1)^2，令w的初值是常数5。反向传播就是求最优w。即求最小loss对应的w值
import tensorflow as tf
#定义待优化参数w初值赋5
w = tf.Variable(tf.constant(5,dtype=tf.float32))
#定义损失函数loss
loss = tf.squre(w+1)
#定义反向传播方法
train_step = tf.train.GradientDescentOptimizer(0.2).minimize(loss)
#定义会话，训练40轮
with tf.Session() as sess:
    init_op = tf.global_variables_initializer()
    sess.run(init_op)
    for i in range(40):
        sess.run(train_step)
        w_val = sess.run(w)
        loss_val = sess.run(loss)
        print "After %s steps: w is %f, loss is %f." % (i, w_val, loss_val)