tensorboard windows 问题解决

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
def add_layer(inputs,in_size,out_size,activation_function=None):
    with tf.name_scope('layer'):
        with tf.name_scope('weights'):
            Weights = tf.Variable(tf.random_normal([in_size,out_size]))
        with tf.name_scope('biases'):
            biases = tf.Variable(tf.zeros([1,out_size])+0.1)
        with tf.name_scope('Wx_plus_b'):
            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)[:,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('input'):
    xs=tf.placeholder(tf.float32,[None,1],name='x_input')#1表示输入是1
    ys=tf.placeholder(tf.float32,[None,1],name='y_input')

l1=add_layer(xs,1,10,activation_function=tf.nn.relu)
prediction=add_layer(l1,10,1,activation_function=None)
with tf.name_scope('loss'):
    loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction),reduction_indices=[1]))
with tf.name_scope('train'):
    train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)


init=tf.initialize_all_variables()
sess=tf.Session()
writer = tf.summary.FileWriter('logs/', sess.graph)####最重要####
sess.run(init)

fig=plt.figure()
ax=fig.add_subplot(1,1,1)
ax.scatter(x_data,y_data)
plt.ion()#连续画图
plt.show()

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}))
        try:
            ax.lines.remove(lines[0])
        except Exception:
            pass
        prediction_value=sess.run(prediction,feed_dict={xs:x_data})
        lines = ax.plot(x_data,prediction_value,'r-',lw=5)
        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：