I use tensorflow 1.2.0
installed with pip install
.
When I run samples that include
import logging
tf.logging.set_verbosity(tf.logging.INFO)
the logging messages of the form
logging.info('TEST')
do not appear in the terminal output, even with the flag --tostderr
.
According to this answer I also tried
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0'
but still the problem persists. Any ideas?
So to knock out these warnings in a single blow, do import warnings then warnings. filterwarnings('ignore') , then run your tensorflow imports and and code that relies on the broken alpha-tensorflow code, then turn warnings back on via warnings. resetwarnings() .
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. get_logger() is used to get the logger instance. Syntax: tensorflow.get_logger() Parameters: It doesn't accept any parameters.
So there is a lot of confusion around tensorflow logging, and it is really not well documented. I landed here a few times in my searches, so it seems to be a good place to post an answer.
After some research and experimentation with Ubuntu and Windows (more than I had planned), this is what I got:
There are two flags, similarly named, but with somewhat different semantics:
TF_CPP_MIN_LOG_LEVEL
- which has 3 or 4 basic levels - low numbers = more messages.
0
outputs Information, Warning, Error, and Fatals (default)1
outputs Warning, and above 2
outputs Errors and above.TF_CPP_MIN_VLOG_LEVEL
- which causes very very many extra Information errors - really for debugging only - low numbers = less messages.
3
Outputs lots and lots of stuff2
Outputs less1
Outputs even less0
Outputs nothing extra (default)python tf-program.py &>mylog.log
os
module so you should be able to set them in the environmentos
module did not pick them up under Windows. Python never loved Windows...
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0'
os.environ['TF_CPP_MIN_VLOG_LEVEL'] = '3'
import tensorflow as tf
TF_CPP_MIN_VLOG_LEVEL=3 python tf-program.py
FWIW, I tested on TensorFlow 1.7 with this tutorial:
https://github.com/tensorflow/models/tree/master/tutorials/image/mnist
And this is what it looks like:
There are really two logging systems in tensorflow: one in the C++ core (specifically tensorflow/core/platform/default/logging.{h,cc}) and the other in the Python bindings. The two systems are independent.
The one in the Python binding plays nicely with the standard Python logging module. The C++ logger is indepedently controlled by the TF_CPP_MIN_LOG_LEVEL
environment variables mentioned in previous answers.
The following Python (that I locally called logtest.py) demonstrates the two systems' independence.
"""
Demonstrate independence of TensorFlow's two logging subsystems.
"""
import argparse
import tensorflow as tf
import logging
_logger = logging.getLogger( "tensorflow" )
parser = argparse.ArgumentParser( description="Demo TensorFlow logging" )
parser.add_argument("-v","--verbosity",
default="",
choices=['DEBUG','INFO','WARNING','ERROR','CRITICAL'],
help="One of {DEBUG,INFO,WARNING,ERROR,CRITICAL}" )
args = parser.parse_args()
print( "Initial Python effective log level:", _logger.getEffectiveLevel() )
# If user provided an explicit Python level, set it.
if args.verbosity:
_logger.setLevel( args.verbosity )
print( " ...new Python effective log level:", _logger.getEffectiveLevel() ) # ...and confirm the change.
_logger.debug( " DEBUG messages are emitted" )
_logger.info( " INFO messages are emitted" )
_logger.warn( " WARNING messages are emitted" )
_logger.error( " ERROR messages are emitted" )
_logger.critical( "CRITICAL messages are emitted" )
with tf.Session() as s:
pass # ...just to trigger TensorFlow into action to generate logging.
Running...
TF_CPP_MIN_LOG_LEVEL=0 python3 logtest.py -v CRITICAL
...shows that Python can't silence the core logging system, and
TF_CPP_MIN_LOG_LEVEL=5 python3 logtest.py -v DEBUG
...shows that the core system can't silence Python.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With