1 import tensorflow as tf
 2 import numpy as np
 3 
 4 '''使用numpy生成100個隨機點'''
 5 x_data = np.random.rand(100)
 6 y_data = x_data*0.1 + 0.2
 7 
 8 '''構造一個線性模型'''
 9 b = tf.Variable(0.)
10 k = tf.Variable(0.)
11 y = k*x_data + b
12 
13 '''二次代價函式'''
14 loss = tf.reduce_mean(tf.square(y_data - y))
15 '''定義一個梯度下降法來進行訓練的優化器
 
'''
16 optimizer = tf.train.GradientDescentOptimizer(0.2)
17 '''最小化代價函式'''
18 train = optimizer.minimize(loss)
19 
20 '''初始化變數'''
21 init = tf.global_variables_initializer()
22 
23 with tf.Session() as sess:
24     sess.run(init)
25     for step in range(201):
26         sess.run(train)
27         if step % 20 == 0:
 
28             print(step, sess.run([k, b]))