import tensorflow as tf
import numpy as np
#create data
x_data = np.random.rand(100).astype(np.float32)
y_data = x_data*0.1+0.3
####create tensorflow structure start###
Weights = tf.Variable(tf.random_uniform([1],-1.0,1.0))
biases = tf.Variable(tf.zeros([1]))
y = Weights*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(Weights),sess.run(biases))
