Tensorboard get blank page

人走茶凉 提交于 2020-06-27 17:41:35

问题


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

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

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)

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

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

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

I also try to use another browser but not works.


回答1:


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




回答2:


The logdir you're pointing tensorboard to probably does not exist (tensorboard does not throw an error in that case). Did you mean tensorboard --logdir=./logs/?




回答3:


This may come late, but hopefully it will help someone else. If your browser does not accept cookies, you will run into this issue. Make sure you allow cookies for the Tensorboard page you are trying to access.




回答4:


It may happen to many reason, when I face this problem, I add port number and check the path :

tensorboard --logdir=run1:/tmp/tensorflow/ --port 6006


来源:https://stackoverflow.com/questions/43279667/tensorboard-get-blank-page

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