tensorflow-简单实例1

import tensorflow as tf

import numpy as np

#create data

x_data = np.random.rand(100).astype(np.float32)

y_data = 0.5*x_data + 1.3

#tensorflow中的变量，这些变量在每次sess迭代时会更新，而那么不是变量的数据不会更新

Weights = tf.Variable(np.random.rand(1))

Biases = tf.Variable(np.zeros((1)))

y = Weights*x_data+Biases

loss = tf.reduce_mean(tf.square(y-y_data))

optimizer= tf.train.GradientDescentOptimizer(0.2)

train = optimizer.minimize(loss)

sess = tf.Session()

init = tf.global_variables_initializer()

sess.run(init)

for i in range(200):

    sess.run(train)
    if(i % 20==0):

#定义为变量的数据必须通过sess来取出，否则输出的是对象

        print(i,sess.run(Weights), sess.run(Biases))