import tensorflow as tf
import numpy as np
x=tf.constant([0.0,0.2,0.4,0.6,0.8],np.float)#给定的x值
y=tf.constant([0.9,1.9,2.8,3.3,4.2])#给定的y值
a=tf.Variable(tf.random_uniform([1],-1.0,1.0))#需要拟合的a
b=tf.Variable(tf.zeros([1]),np.float)#需要拟合的b
Y=a*x+b
los=tf.reduce_mean(tf.square(y-Y))
op=tf.train.GradientDescentOptimizer(0.5)#学习率为0.5
train=op.minimize(los)
init=tf.initialize_all_variables()
ini=tf.global_variables_initializer() #对变量初始化
print("开始run")
with tf.Session() as sess:
sess.run(init)
for step in range(201): #进行200次训练
sess.run(train)
if step%20==0: #每20次输出拟合的a,b
print(step,sess.run(a),sess.run(b))
print("结束")
