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# View more python tutorial on my Youtube and Youku channel!!!

# Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg

# Youku video tutorial: http://i.youku.com/pythontutorial

"""

Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.

"""

from __future__ import print_function

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)

### create tensorflow structure end ###

sess = tf.Session()

# tf.initialize_all_variables() no long valid from

# 2017-03-02 if using tensorflow >= 0.12

if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:

init = tf.initialize_all_variables()

else:

init = tf.global_variables_initializer()

sess.run(init)

for step in range(201):

sess.run(train)

if step % 20 == 0:

print(step, sess.run(Weights), sess.run(biases))