tensorflow 莫烦 二次函数弥拟合（四）

# -*- coding: utf-8 -*-
"""
Created on Wed Apr 19 22:24:49 2017

@author: user
"""


import tensorflow as tf
import numpy as np


def add_layer(inputs,in_size,out_size,activation_function=None):

    Weights=tf.Variable(tf.random_normal([in_size,out_size]))   

    biases=tf.Variable(tf.zeros([1,out_size])+0.1) 

    Wx_plus_b=tf.matmul(inputs,Weights)+biases

    if activation_function is None:
        outputs=Wx_plus_b
    else:
        outputs=activation_function(Wx_plus_b)  

    return outputs          


x_data=np.linspace(-1,1,300,dtype=np.float32)[:,np.newaxis] 

noise=np.random.normal(0,0.05,x_data.shape).astype(np.float32)

y_data=np.square(x_data)-0.5+noise   

xs=tf.placeholder(tf.float32,[None,1])
ys=tf.placeholder(tf.float32,[None,1])

l1=add_layer(x_data,1,10,activation_function=tf.nn.relu)

prediction =  add_layer(l1,10,1,activation_function=None)

loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction),reduction_indices=[1]))

train_step=tf.train.GradientDescentOptimizer(0.01).minimize(loss)

init=tf.initialize_all_variables()

sess=tf.Session()


sess.run(init)

for i in range(1000):
    sess.run(train_step,feed_dict={xs:x_data,ys:y_data})

    if i%50==0:
        print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))