打开Tensorboard的具体方法【windows环境】

Tensorboard试了一下午都打不开.错误情况是：

connectex: Therequested address is not valid in its context.

后来得大神指点总算知道自己错在哪里，特来分享一下。

1.首先，我在E盘新建了一个文件夹名为logs。

python代码保存位置为E:\code，具体内容如下：

"""
Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.
"""
from __future__ import print_function
import tensorflow as tf


def add_layer(inputs, in_size, out_size, activation_function=None):
    # add one more layer and return the output of this layer
    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('inputs'):
    xs = tf.placeholder(tf.float32, [None, 1], name='x_input')
    ys = tf.placeholder(tf.float32, [None, 1], name='y_input')

# 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 prediciton and real data
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)

sess = tf.Session()

# tf.train.SummaryWriter soon be deprecated, use following
if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:  # tensorflow version < 0.12
    writer = tf.train.SummaryWriter('E:/logs/', sess.graph)
else:  # tensorflow version >= 0.12
    writer = tf.summary.FileWriter("E:/logs/", sess.graph)

# tf.initialize_all_variables() no long valid from
# 2017-03-02 if using tensorflow >= 0.12
if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
    init = tf.initialize_all_variables()
else:
    init = tf.global_variables_initializer()
sess.run(init)

2.跑一下上述代码，在文件夹E:/logs中生成日志文件。 
然后打开cmd，首先进入刚才保存代码的文件夹，即E:\code.这一步至关重要，若未在此文件夹下进行后续操作，即使打开tensorboard也会出现一片空白，空白如下图。

3.在终端中输入命令 
       tensorboard --logdir=E:\logs 

系统会给你一个网址，可是千万不要单纯的把http://0.0.0.0:6006输入自己的浏览器地址栏里，否则就会出现文章开始我说的那个错误，就是下面这样 

而应该在浏览器地址栏里输入的是http://127.0.0.1:6006    
其中127.0.0.1是你的localhost，具体是什么我也不知道，总之你百度一下localhost它会出现百度百科，然后告诉你是127.0.0.1.

最后tensorboard就打开了！图也有了！大功告成。