Tensorboard 获取空白页 [英] Tensorboard get blank page

问题描述

我是 tensorflow 的新手，我关注这个 教程 以了解此框架.

I'm new in tensorflow and i follow this tutorial to learn about this framework.

现在我正在尝试使用 Tensorboard 来可视化我的图表，但是我得到了一个 tensorboard 空白页面，但没有任何结果.

Now i'm trying to visualize my graph using Tensorboard but but i get a tensorboard blank page without any result.

我用来可视化图表的代码是:

The code that i use to visualize the graph is:

from __future__ import print_function
import tensorflow as tf
import numpy as np


def add_layer(inputs, in_size, out_size, n_layer,     activation_function=None):
# add one more layer and return the output of this layer
layer_name = 'layer%s' % n_layer
with tf.name_scope(layer_name):
    with tf.name_scope('weights'):
        Weights = tf.Variable(tf.random_normal([in_size, out_size]), name='W')
        tf.summary.histogram(layer_name + '/weights', Weights)
    with tf.name_scope('biases'):
        biases = tf.Variable(tf.zeros([1, out_size]) + 0.1, name='b')
        tf.summary.histogram(layer_name + '/biases', biases)
    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, )
    tf.summary.histogram(layer_name + '/outputs', outputs)
return outputs


# Make up some real data
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

# 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, n_layer=1, activation_function=tf.nn.relu)
# add output layer
prediction = add_layer(l1, 10, 1, n_layer=2, 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]))
    tf.summary.scalar('loss', loss)

with tf.name_scope('train'):
     train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

sess = tf.Session()
merged = tf.summary.merge_all()

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

init = tf.global_variables_initializer()
sess.run(init)

for i in range(1000):
    sess.run(train_step, feed_dict={xs: x_data, ys: y_data})
    if i % 50 == 0:
        result = sess.run(merged,
                      feed_dict={xs: x_data, ys: y_data})
        writer.add_summary(result, i)

我使用 Ubuntu 16.04 和 python 2.7，我的 tensorflow 版本是 1.0.1.

I'm using Ubuntu 16.04 with python 2.7 and my tensorflow version is 1.0.1.

当我运行程序时会创建一个新的日志文件，然后我使用 theis 命令来可视化张量板:

When i run the program is created a new log file, and after that i use theis command to visualize the tensorboard:

 tensorboard --logdir=/logs

然后如果我去http://127.0.1.1:6006/strong> 得到没有任何摘要的 Tensorboard 页面，为什么?

then if i go to http://127.0.1.1:6006/ get the Tensorboard page without any summary, why?

我也尝试使用其他浏览器，但不起作用.

I also try to use another browser but not works.

推荐答案

您将保存到运行 ipython 笔记本的位置的日志文件夹.但是，您的 Tensorboard 会尝试加载/logs 文件夹(而不是/users/something/logs).尝试使用 --logdir=./logs

You are saving to the logs folder at the place where you are running your ipython notebook. However, your Tensorboard tries to load the /logs folder (instead of /users/something/logs). Try it with --logdir=./logs

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