tensorboard windows 问题解决 

 1 import tensorflow as tf
 2 import numpy as np
 3 import matplotlib.pyplot as plt
 4 def add_layer(inputs,in_size,out_size,activation_function=None):
 5     with tf.name_scope('layer'):
 6         with tf.name_scope('weights'):
 7             Weights = tf.Variable(tf.random_normal([in_size,out_size]))
 8         with tf.name_scope('biases'):
 9             biases = tf.Variable(tf.zeros([1,out_size])+0.1)
10         with tf.name_scope('Wx_plus_b'):
11             Wx_plus_b = tf.matmul(inputs,Weights)+biases
12         if activation_function is None:
13             outputs = Wx_plus_b
14         else:
15             outputs=activation_function(Wx_plus_b)
16         return outputs
17 
18 x_data=np.linspace(-1,1,300)[:,np.newaxis]
19 noise = np.random.normal(0,0.05,x_data.shape)
20 y_data=np.square(x_data)-0.5+noise
21 
22 
23 with tf.name_scope('input'):
24     xs=tf.placeholder(tf.float32,[None,1],name='x_input')#1表示输入是1
25     ys=tf.placeholder(tf.float32,[None,1],name='y_input')
26 
27 l1=add_layer(xs,1,10,activation_function=tf.nn.relu)
28 prediction=add_layer(l1,10,1,activation_function=None)
29 with tf.name_scope('loss'):
30     loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction),reduction_indices=[1]))
31 with tf.name_scope('train'):
32     train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)
33 
34 
35 init=tf.initialize_all_variables()
36 sess=tf.Session()
37 writer = tf.summary.FileWriter('logs/', sess.graph)####最重要####
38 sess.run(init)
39 
40 fig=plt.figure()
41 ax=fig.add_subplot(1,1,1)
42 ax.scatter(x_data,y_data)
43 plt.ion()#连续画图
44 plt.show()
45 
46 for i in range(1000):
47     sess.run(train_step,feed_dict={xs:x_data,ys:y_data})
48     if i %50==0:
49         # print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))
50         try:
51             ax.lines.remove(lines[0])
52         except Exception:
53             pass
54         prediction_value=sess.run(prediction,feed_dict={xs:x_data})
55         lines = ax.plot(x_data,prediction_value,'r-',lw=5)
56         plt.pause(0.1)

 

 

 

常见问题如下：

  1. ：tf.summary.FileWriter('logs/', sess.graph)  这是正确写法，不能写成writer = tf.train.SummaryWriter('logs/', sess.graph)会报错
  2. 生成logs文件后，cmd到logs文件夹下的路径  执行以下

       

　　3：在chrome浏览器中输入http://localhost:6006

　　4：打开tensorboard中点击GRAPHS即可得到网络可视图，如下：

                                                                                  

   

 

posted @ 2017-08-03 17:45  清风徐来xyd  阅读(211)  评论(0)  编辑  收藏  举报