import tensorflow as tf
import numpy as np 

#create data
x_data = np.random.rand(200).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(0.1)  
train = optimizer.minimize(loss)

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

sess = tf.Session()
sess.run(init)   # very importtant


for step in range(10201):
	sess.run(train)
	if step % 20 == 0:
		print(step, sess.run(Weights), sess.run(biases))



