TF：Tensorflow结构简单应用，随机生成100个数，利用Tensorflow训练使其逼近已知线性直线的效率和截距—Jason niu

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = ''
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                      

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 structure end ###

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

for step in range(201):
    sess.run(train)
    if step % 10 == 0:
        print(step, sess.run(Weights), sess.run(biases))