Question

我有一个似乎在Keras没有直接解决方案的问题。我的服务器在ubuntu 14.04上运行，keras使用后端tensorflow。

问题在于：

我想使用tensorboard绘制直方图，其他训练指标图。我按照以下程序执行此操作。

我ssh到远程GPU服务器并使用以下命令行启动了tensorboard：
```
<-
```

此外，它还生成了以下输出

tensorboard --port 13987 --log==/home/tharun/Desktop/logs

然后我ssh到远程服务器使用以下命令行在该系统上打开firefox

tensorboard --port 13987 --log==/home/tharun/Desktop/logs
/home/tharun/anaconda2/lib/python2.7/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
TensorBoard 0.4.0rc3 at http://sidh-pc:13987 (Press CTRL+C to quit)

在打开的firefox浏览器http://sidh-pc:13987中输入并打开了tensorboard页面。以下信息显示在窗口中。
```
ssh -X tharun@172.26.175.67 firefox -no-remote
```

我在链接https://github.com/tensorflow/tensorboard检查了tensorboard readme.txt。然后我在终端输入以下命令并收到输出：

No dashboards are active for the current data set.

Probable causes:

You haven’t written any data to your event files.
TensorBoard can’t find your event files. 

If you’re new to using TensorBoard, and want to find out how to add data and set up your event files, check out the README and perhaps the TensorBoard tutorial.

If you think TensorBoard is configured properly, please see the section of the README devoted to missing data problems and consider filing an issue on GitHub.

Last reload: Tue Jan 16 2018 18:17:12 GMT+0530 (IST)

Log directory: =/home/tharun/Desktop/logs

在检查器模式下运行tensororboard以检查事件文件的内容。

(deep-learning) tharun@sidh-pc:~$
find /home/tharun/Desktop/logs/ | grep tfevents
/home/tharun/Desktop/logs/events.out.tfevents.1516101897.sidh-pc
/home/tharun/Desktop/logs/events.out.tfevents.1516101849.sidh-pc

在下一阶段，运行以下脚本（位于/ home / tharun / Desktop /）以生成更多事件文件并在tensorboard中绘制结果

(deep-learning) tharun@sidh-pc:~$
tensorboard --inspect --logdir /home/tharun/Desktop/logs
/home/tharun/anaconda2/lib/python2.7/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
======================================================================
Processing event files... (this can take a few minutes)
======================================================================

Found event files in:
/home/tharun/Desktop/logs

These tags are in /home/tharun/Desktop/logs:
audio -
histograms
   dense_1/bias_0
   dense_1/bias_0_grad
   dense_1/kernel_0
   dense_1/kernel_0_grad
   dense_1_out
   dense_2/bias_0
   dense_2/bias_0_grad
   dense_2/kernel_0
   dense_2/kernel_0_grad
   dense_2_out
   dense_3/bias_0
   dense_3/bias_0_grad
   dense_3/kernel_0
   dense_3/kernel_0_grad
   dense_3_out
images -
scalars
   acc
   loss
   val_acc
   val_loss
tensor -
======================================================================

Event statistics for /home/tharun/Desktop/logs:
audio -
graph
   first_step           0
   last_step            0
   max_step             0
   min_step             0
   num_steps            1
   outoforder_steps     []
histograms
   first_step           0
   last_step            149
   max_step             149
   min_step             0
   num_steps            150
   outoforder_steps     []
images -
scalars
   first_step           0
   last_step            149
   max_step             149
   min_step             0
   num_steps            150
   outoforder_steps     []
sessionlog:checkpoint -
sessionlog:start -
sessionlog:stop -
tensor -
======================================================================

(deep-learning) tharun@sidh-pc:~$

张量板窗口的状态没有变化。因此，我重新启动了tensorboard服务器并完成了上述类似的过程。但是firefox中的tensorboard窗口仍显示相同的状态日志：

from keras.models import Sequential
from keras.layers import Dense
import numpy
from keras.callbacks import TensorBoard
from time import time
# fix random seed for reproducibility
numpy.random.seed(7)
# load pima indians dataset
dataset = numpy.loadtxt("pima-indians-diabetes.csv", delimiter=",")
# split into input (X) and output (Y) variables
X = dataset[:,0:8]
Y = dataset[:,8]
# create model
model = Sequential()
model.add(Dense(12, input_dim=8, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
# Compile model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
tensorboard =TensorBoard(log_dir='./logs', histogram_freq=1, batch_size=1, write_graph=True, write_grads=True, write_images=False, embeddings_freq=0, embeddings_layer_names=None, embeddings_metadata=None)

# Fit the model
model.fit(X, Y, epochs=150, batch_size=10, validation_split=0.2, verbose=1, callbacks=[tensorboard])
# evaluate the model
scores = model.evaluate(X, Y)
print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))

Answer 1

终端中的以下一行做了伎俩!!目前位于/ home / tharun / Desktop /目录

tensorboard --logdir=./
/home/tharun/anaconda2/lib/python2.7/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
TensorBoard 0.4.0rc3 at http://sidh-pc:6006 (Press CTRL+C to quit)
W0117 22:24:07.582409 Reloader plugin_event_accumulator.py:303] Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
W0117 22:24:42.635272 Reloader plugin_event_accumulator.py:311] Found more than one metagraph event per run. Overwriting the metagraph with the newest event.

让tensorboard与keras一起工作

1 个答案: