import tensorflow as tf
import numpy as np


x_data=np.random.rand(100).astype(np.float32)
y_data=x_data*0.1+0.3;

### create tensorflow structure ###

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()
init =  tf.global_variables_initializer()
### create tensorflow end ###


### start training

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

for step in range(501):
	sess.run(train)
	if step%20==0:
		print (step,sess.run(Weights),sess.run(biases))
