tensorboard显示没有内容

时间:2016-06-04 04:36:29

标签: python tensorflow tensorboard

我对张量板有问题。我的代码运行正常,当我尝试使用tensorboard --logdir = logs / log1可视化图形,然后打开浏览器输入localhost:6006我看到没有内容的页面(只有tensorboard标志和标签,如事件,图形.. 。) 非常感谢帮助。不知道如何解决问题。 (我正在使用jupyter笔记本)

以下是我收到的错误消息:

WARNING:tensorflow:IOError [Errno 2] No such file or directory:       '/home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-   packages/tensorflow/tensorboard/TAG' on path /home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/tensorboard/TAG
WARNING:tensorflow:Unable to read TensorBoard tag
Starting TensorBoard  on port 6006
(You can navigate to http://0.0.0.0:6006)
127.0.0.1 - - [03/Jun/2016 21:20:49] "GET / HTTP/1.1" 200 -
WARNING:tensorflow:IOError [Errno 2] No such file or directory: '/home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/tensorboard/lib/css/global.css' on path /home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/tensorboard/lib/css/global.css
127.0.0.1 - - [03/Jun/2016 21:20:49] code 404, message Not Found
127.0.0.1 - - [03/Jun/2016 21:20:49] "GET /lib/css/global.css HTTP/1.1" 404 -
127.0.0.1 - - [03/Jun/2016 21:20:50] "GET /external/lodash/lodash.min.js HTTP/1.1" 200 -
.......
WARNING:tensorflow:IOError [Errno 2] No such file or directory: '/home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/tensorboard/favicon.ico' on path /home/tiger/anaconda3/envs/tensorflow/lib/python3.5/site-packages/tensorflow/tensorboard/favicon.ico

我的代码如下:

n_features = x_train.shape[1]
n_samples = x_train.shape[0]
n_labels = 10
n_hidden = 200
epoch_train = 200
learning_rate = 0.01
batch_size = 20

x_tr = tf.placeholder(tf.float32, shape=(None, n_features), name='x')
y_tr = tf.placeholder(tf.float32, shape=(None, n_labels), name='y')

w1 = tf.Variable(tf.truncated_normal([n_features,n_hidden]),name='weight1')
b1 = tf.Variable (tf.zeros([n_hidden]), name='bias1')
w2 = tf.Variable (tf.truncated_normal([n_hidden, n_labels]),name ='weight2')
b2 = tf.Variable(tf.zeros([n_labels]), name='bias2')

w1_hist = tf.histogram_summary('weight1', w1)
w2_hist = tf.histogram_summary('weight2', w2)
b1_hist = tf.histogram_summary('bias1', b1)
b2_hist = tf.histogram_summary('bias2', b2)
y_hist = tf.histogram_summary('y', y_tr)

with tf.name_scope('hidden') as scope:    
    z1 = tf.matmul(x_tr, w1)+b1
    a1 = tf.nn.relu (z1)

with tf.name_scope('output') as scope:    
    z2 = tf.matmul(a1, w2)+b2
    a2 = tf.nn.softmax (z2)

with tf.name_scope('cost') as scope:
    loss = tf.reduce_mean (tf.nn.softmax_cross_entropy_with_logits(z2, y_tr))
    cost_summ = tf.scalar_summary ('cost', loss)

with tf.name_scope('train') as scope:
    optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(loss)

def acc (pred, y):
     return (np.mean(np.argmax(pred, 1)==np.argmax(y,1)))


with tf.Session() as session:

session.run(tf.initialize_all_variables())

merged = tf.merge_summary([y_hist, w1_hist, w2_hist, b1_hist, b2_hist, cost_summ])
writer = tf.train.SummaryWriter ('logs/log1', session.graph)

for epoch in range (epoch_train):

    offset = epoch*batch_size % (x_train.shape[0]-batch_size)
    x_tr_batch = x_train[offset:offset+batch_size, :]
    y_tr_batch = y_train[offset:offset+batch_size, :]
    feed_dict = {x_tr:x_tr_batch, y_tr:y_tr_batch}

    _, cost, prediction = session.run ([optimizer, loss, a2], feed_dict=feed_dict)

    summary = session.run (merged, feed_dict=feed_dict)
    writer.add_summary(summary,epoch)

    if epoch % 20 ==0:
        print ('training accuracy:', acc(prediction, y_tr_batch))
        print ('cost at epoch {} is:'.format(epoch), cost)
pred_ts = session.run (a2, feed_dict = {x_tr:x_test})
print ('test accuracy is:', acc(pred_ts, y_test))

4 个答案:

答案 0 :(得分:3)

您可以通过编写以下命令来访问tensorboard: tensorboard --logdir =“您的模型临时目录”--host = 127.0.0.1

现在在您的浏览器中打开127.0.0.1:6006,您将在tensorboard上有内容。 我希望这能解决你的问题。

答案 1 :(得分:0)

看起来问题与this issue有关。确保在运行程序后启动tensorboard。还要看看其他人做了什么来解决它。它可能是张量板中的错误。你想从源代码构建张量流吗?

答案 2 :(得分:0)

你得到的错误不会打扰我。我想问题是你什么都没写。您可以尝试在add_summary()行之后添加此行{{1}}。

答案 3 :(得分:0)

如果您确实看到了标签,但没有看到标签"嵌入",您可能会有旧版本的tensorflow / tensorboard。尝试升级到1.0,这对我有用!