tensorflow基础

import tensorflow as tf
import numpy as np
#create data
x_data=np.random.rand(10000).astype(np.float32)
y_data=0.1*x_data+0.3

###create tensorflow structure start ###
Weights=tf.Variable(tf.random_uniform([1],-1,1))
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 struct end###
sess=tf.Session()
sess.run(init)  #Very important
for step in range(2010):
    sess.run(train)
    if step %20==0:
        print(step,sess.run(Weights),sess.run(biases))