basic_curve.py

# -*- coding: utf-8 -*-
#模拟曲线
#http://www.jianshu.com/p/fe586964ab07

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
def add_layer(layoutname,inputs,in_size,out_size,activatuib_funaction=None):

    #with tf.name_scope指定tensorboard中layer名称，否则生成后是layer1，layer2这种。
    with tf.name_scope(layoutname):
        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 activatuib_funaction is None:
            outputs=Wx_plus_b
        else :
            outputs=activatuib_funaction(Wx_plus_b)
        return outputs

x_data=np.linspace(-1,1,300)[:,np.newaxis]
noise=np.random.normal(0,0.05,x_data.shape)
y_data=np.square(x_data)-0.5+noise

#with tf.name_scope指定tensorboard中layer名称
with tf.name_scope('inputs'):
    xs=tf.placeholder(tf.float32,[None,1])
    ys=tf.placeholder(tf.float32,[None,1])


l1=add_layer("first_layer",xs,1,10,activatuib_funaction=tf.nn.relu)
predition=add_layer('second_layout',l1,10,1,activatuib_funaction=None)

with tf.name_scope('loss'):
    loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-predition),reduction_indices=[1]))
with tf.name_scope('train'):
    train_step=tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init=tf.global_variables_initializer()

with tf.Session() as sess:
    fig=plt.figure()
    ax=fig.add_subplot(1,1,1)
    ax.scatter(x_data,y_data)
    plt.show(block=False)

    writer=tf.summary.FileWriter("logs/",sess.graph)
    sess.run(init)

    for train in range(5000):

        sess.run(train_step,feed_dict={xs:x_data,ys:y_data})
        if train%50==0:

            try:
                ax.lines.remove(lines[0])
            except Exception:
                pass
            print train,sess.run(loss,feed_dict={xs:x_data,ys:y_data})
            predition_value=sess.run(predition,feed_dict={xs:x_data})
            lines=ax.plot(x_data,predition_value,'r-',lw=5)
            plt.pause(0.1)

#为了让程序保持运行，增加以下代码
while(True):
    a=1