This question already has an answer here:
- Disable Tensorflow debugging information 9 answers
I'm unittesting my Tensorflow code with nosetests but it produces such amount of verbose output that makes it useless.
The following test
import unittest
import tensorflow as tf
class MyTest(unittest.TestCase):
def test_creation(self):
self.assertEquals(True, False)
when run with nosetests creates a huge amount of useless logging:
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.
......
whereas using tensorflow from the ipython console doesn't seem that verbose:
$ 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]:
How could I suppress the former logging when running nosetests?
v0.12+ Update (5/20/17), Working through TF 2.0 alpha:
In TensorFlow 0.12+, per this issue, you can now control logging via the environmental variable called TF_CPP_MIN_LOG_LEVEL; it defaults to 0 (all logs shown) but can be set to one of the following values under the Level column.
Level | Level for Humans | Level Description
-------|------------------|------------------------------------
0 | DEBUG | [Default] Print all messages
1 | INFO | Filter out INFO messages
2 | WARNING | Filter out INFO & WARNING messages
3 | ERROR | Filter out all messages
See the following generic OS example using Python:
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
import tensorflow as tf
To be thorough, you call also set the level for the Python tf_logging module, which is used in e.g. summary ops, tensorboard, various estimators, etc.
# append to lines above
tf.logging.set_verbosity(tf.logging.ERROR) # or any {DEBUG, INFO, WARN, ERROR, FATAL}
For Prior Versions of TensorFlow or TF-Learn Logging (v0.11.x or lower):
View the page below for information on TensorFlow logging; with the new update, you're able to set the logging verbosity to either DEBUG, INFO, WARN, ERROR, or FATAL. For example:
tf.logging.set_verbosity(tf.logging.ERROR)
The page additionally goes over monitors which can be used with TF-Learn models. Here is the page.
This doesn't block all logging, though (only TF-Learn). I have two solutions; one is a 'technically correct' solution (Linux) and the other involves rebuilding TensorFlow.
script -c 'python [FILENAME].py' | grep -v 'I tensorflow/'
For the other, please see this answer which involves modifying source and rebuilding TensorFlow.
Running the tests with nosetests --nologcapture will disable the display of these logs.
More information about the logging for nosetests:
https://nose.readthedocs.io/en/latest/plugins/logcapture.html
Here's an example of doing this. Unfortunately this requires modifying the source and rebuilding. Here's a tracking bug to make it easier
来源：https://stackoverflow.com/questions/38073432/how-to-suppress-verbose-tensorflow-logging