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Comment supprimer la journalisation Tensorflow verbeuse?

Je ne teste pas mon code Tensorflow avec nosetests mais il produit une telle quantité de sortie verbeuse qui le rend inutile.

Le test suivant

import unittest
import tensorflow as tf

class MyTest(unittest.TestCase):

    def test_creation(self):
        self.assertEquals(True, False)

lorsqu'il est exécuté avec nosetests crée une énorme quantité de journalisation inutile:

FAIL: test_creation (tests.test_tf.MyTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/cebrian/GIT/thesis-nilm/code/deepmodels/tests/test_tf.py", line 10, in test_creation
    self.assertEquals(True, False)
AssertionError: True != False
-------------------- >> begin captured logging << --------------------
tensorflow: Level 1: Registering Const (<function _ConstantShape at 0x7f4379131c80>) in shape functions.
tensorflow: Level 1: Registering Assert (<function no_outputs at 0x7f43791319b0>) in shape functions.
tensorflow: Level 1: Registering Print (<function _PrintGrad at 0x7f4378effd70>) in gradient.
tensorflow: Level 1: Registering Print (<function unchanged_shape at 0x7f4379131320>) in shape functions.
tensorflow: Level 1: Registering HistogramAccumulatorSummary (None) in gradient.
tensorflow: Level 1: Registering HistogramSummary (None) in gradient.
tensorflow: Level 1: Registering ImageSummary (None) in gradient.
tensorflow: Level 1: Registering AudioSummary (None) in gradient.
tensorflow: Level 1: Registering MergeSummary (None) in gradient.
tensorflow: Level 1: Registering ScalarSummary (None) in gradient.
tensorflow: Level 1: Registering ScalarSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering MergeSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering AudioSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering ImageSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering HistogramSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering HistogramAccumulatorSummary (<function _ScalarShape at 0x7f4378f042a8>) in shape functions.
tensorflow: Level 1: Registering Pack (<function _PackShape at 0x7f4378f047d0>) in shape functions.
tensorflow: Level 1: Registering Unpack (<function _UnpackShape at 0x7f4378f048c0>) in shape functions.
tensorflow: Level 1: Registering Concat (<function _ConcatShape at 0x7f4378f04938>) in shape functions.
tensorflow: Level 1: Registering ConcatOffset (<function _ConcatOffsetShape at 0x7f4378f049b0>) in shape functions.

......

alors que l'utilisation de tensorflow depuis la console ipython ne semble pas aussi verbeuse:

$ ipython
Python 2.7.11+ (default, Apr 17 2016, 14:00:29) 
Type "copyright", "credits" or "license" for more information.

IPython 4.2.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]: import tensorflow as tf
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so locally
I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally

In [2]:

Comment pourrais-je supprimer l'ancien enregistrement lors de l'exécution de nosetests?

tensorflowdeep-learningnose
16
tonicebrian

Exécution des tests avec nosetests --nologcapture désactivera l'affichage de ces journaux. Plus d'informations sur la journalisation pour nosetests: https://nose.readthedocs.io/en/latest/plugins/logcapture.html

9
mjp

Voici n exemple de faire cela. Malheureusement, cela nécessite de modifier la source et de reconstruire. Voici un bug de suivi pour le rendre plus facile

0
Yaroslav Bulatov