在anaconda的spyder下生成logs檔案後在chrome瀏覽器中開啟tensorboard，可以看到自己搭建的框架。
總結一下過程與遇到的問題：
1，程式碼中python3.6原來函式改變為tf.summary.FileWriter、tf.global_variables_initializer()。不然報錯無法生成logs檔案
2.生成後，在logs檔案那層，按住shift+右鍵，開啟cmd(可以省去cd到該層目錄的過程),輸入命令：tensorboard –logdir logs

開啟chrome瀏覽器，不要輸入他的http….（試了很多次不行，坑）
輸入localhost：6006

測試程式碼：

# -*- coding: utf-8 -*-
"""
Created on Mon Dec 25 19:53:43 2017

@author: Administrator
"""

import matplotlib.pyplot as plt
import time
import tensorflow as tf
import numpy as np
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]),name='W')
        with tf.name_scope('biases'):  
            biases=tf.Variable(tf.zeros([1,out_size])+0.1,name='b')
        with tf.name_scope('Wx_plus_b'):
            Wx_plus_b=tf.add(tf.matmul(inputs,Weights),biases)
        if
 
 activation_function is None:
            outputs=Wx_plus_b
        else:
            outputs=activation_function(Wx_plus_b)
        return outputs
#define placeholder for inputs to network
with tf.name_scope('inputsdong'):
    xs=tf.placeholder(tf.float32,[None,1],name='x_inputdong')
    ys=tf.placeholder(tf.float32,[None,1],name='y_inputdong')

#add hidden layer
l1=add_layer(xs,1,10,activation_function=tf.nn.relu)
#add output layer
prediction=add_layer(l1,10,1,activation_function=None)
#the error between prediction and real data 
loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction),reduction_indices=[1]))
with tf.name_scope('traindong'):
    train_step=tf.train.GradientDescentOptimizer(0.1).minimize(loss)
sess=tf.Session()

writer=tf.summary.FileWriter("logs/",sess.graph)
#important step
sess.run(tf.global_variables_initializer())