Sind scalar_summary in skflow verpasst?

Question

ich Problem mit dem Verlust (Ausbildung oder Überwachung) Zusammenfassung in tensorboard skflow meinen Code

Dies ist

mit zeigen zu bekommen:

classifier = skflow.TensorFlowEstimator( model_fn=conv_model, n_classes=2, batch_size=BATCH_SIZE, steps=100000, learning_rate=0.001, config=RunConfig(gpu_memory_fraction=0.9)) 

val_monitor = monitors.ValidationMonitor(X_val, y_val, n_classes=2, print_steps=100) 

classifier.fit(X_train, y_train, val_monitor, logdir='my_model_1/') 

classifier.save('my_model_1/') 

Alles läuft gut:

`I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcublas.so locally 
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcudnn.so locally 
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcufft.so locally 
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcuda.so.1 locally 
I tensorflow/stream_executor/dso_loader.cc:105] successfully opened CUDA library libcurand.so locally 
/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/io/data_feeder.py:281: VisibleDeprecationWarning: converting an array with ndim > 0 to an index will result in an error in the future 
    out.itemset((i, self.y[sample]), 1.0) 
I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties: 
name: GeForce GTX 980 
major: 5 minor: 2 memoryClockRate (GHz) 1.253 
pciBusID 0000:03:00.0 
Total memory: 4.00GiB 
Free memory: 3.91GiB 
I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0 
I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y 
I tensorflow/core/common_runtime/gpu/gpu_device.cc:755] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 980, pci bus id: 0000:03:00.0) 
/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/io/data_feeder.py:370: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future 
    out.itemset((i, y), 1.0) 
Step #99, avg. train loss: 2.22587, avg. val loss: 2.14521 
Step #199, avg. train loss: 0.82641, avg. val loss: 0.89103 
Step #299, avg. train loss: 0.78344, avg. val loss: 0.85636 
Step #399, avg. train loss: 0.76420, avg. val loss: 0.85675 
Step #499, avg. train loss: 0.75868, avg. val loss: 0.84104 
Step #599, avg. train loss: 0.75467, avg. val loss: 0.84945 
Step #699, avg. train loss: 0.73990, avg. val loss: 0.91238 
Step #799, avg. train loss: 0.73400, avg. val loss: 0.92720 
Step #899, avg. train loss: 0.72879, avg. val loss: 0.91054 
Step #999, avg. train loss: 0.73448, avg. val loss: 0.89823 
Step #1099, avg. train loss: 0.70125, avg. val loss: 0.91640 
Step #1199, avg. train loss: 0.71879, avg. val loss: 0.90597 
Step #1299, avg. train loss: 0.70713, avg. val loss: 0.90736 
Step #1399, avg. train loss: 0.70023, avg. val loss: 0.91414 
Step #1499, avg. train loss: 0.69566, avg. val loss: 0.91007 
Step #1599, avg. train loss: 0.68030, avg. val loss: 0.92729 
Step #1699, avg. train loss: 0.68919, avg. val loss: 0.91168 
Step #1799, avg. train loss: 0.67088, avg. val loss: 0.91744 
Step #1899, avg. train loss: 0.68732, avg. val loss: 0.88844 
Step #1999, avg. train loss: 0.67585, avg. val loss: 0.88854` 

es erzeugt die Datei .tfevents, die 4,8M Größe (angeschlossen) haben

wenn ich an die Maschine mit Chrom als Explorer ich habe verbinden Daten in Graphen/Histogrammen/aber nichts in Ereignissen (Es wurden keine skalaren Daten gefunden)

habe ich etwas vermisst, um den Verlust protokolliert zu haben?

NB: Ich habe logging_ops.scalar_summary("model_loss", self._model_loss) in lernen/Python/lernen/Schätzer/base.py und das Modell-Verlust wird in tensorboard

Ps erscheinen: Ich auf GPU Maschine renne tensorflow mit dem letzten Build angebracht tfevents my_model_1.zip

Answer 1

Es wurde ein Problem behoben, in skflow here, und auch für die Überwachung der Validierung here