tensorflow 158 11-1

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt

x_data=np.random.rand(10)
y_data=x_data*0.3+0.15

weight=tf.Variable(0.5)
bias=tf.Variable(0.0)
y_model=weight*x_data+bias

loss=tf.pow((y_model-y_data),2)
train_op=tf.train.GradientDescentOptimizer(0.01).minimize(loss)

sess=tf.Session()
init=tf.initialize_all_variables()
sess.run(init)

for _ in range(200):
    sess.run(train_op)
    print(weight.eval(sess),bias.eval(sess))
plt.plot(x_data,y_data,'ro',label='original data')
plt.plot(x_data,sess.run(weight)*x_data+sess.run(bias),label='Fitted line')
plt.legend()
plt.show()