# -*- coding: utf-8 -*-
"""
Created on Tue Aug 29 13:54:02 2017

@author: dell
"""

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

# create data
x_data = np.random.rand(100).astype(np.float32)

y_data=x_data*0.1+0.3

### create tensorflow structure start ###
Weight = tf.Variable(tf.random_uniform([1],-1.0,1.0))
biases = tf.Variable(tf.zeros([1]))

y = Weight * x_data + biases

loss = tf.reduce_mean(tf.square(y-y_data))

optimizer = tf.train.GradientDescentOptimizer(0.5)


train = optimizer.minimize(loss)

init = tf.initialize_all_variables()
### create tensorflow structure end ###


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


for step in range(201):
    
    sess.run(train)
    if step % 20 == 0:
        print(step,sess.run(Weight),sess.run(biases))




