Python package to shut up TensorFlow warnings and logs, letting you focus on the important errors.
As usual, just download it using pip:
pip install silence_tensorflow
You only need to import the package before importing TensorFlow:
from silence_tensorflow import silence_tensorflow
silence_tensorflow()
import tensorflow as tf
# your code
While by default the logging level is set to error, you can set it to any level you want by passing the level as an argument to the function.
from silence_tensorflow import silence_tensorflow
# Set the logging level to error, meaning only errors will be logged
silence_tensorflow("ERROR")
# Set the logging level to warning, meaning only errors and warnings will be logged
silence_tensorflow("WARNING")
# Set the logging level to info, meaning errors, warnings and info will be logged
silence_tensorflow("INFO")
# Set the logging level to debug, meaning all logs will be shown
silence_tensorflow("DEBUG")
Sure, you can do everything with a single line by importing the submodule auto.
This will set the logging level to error and the affinity to no verbose.
import silence_tensorflow.auto
import tensorflow as tf
# your code
You can use the flag disable=unused-import
as such:
import silence_tensorflow.auto # pylint: disable=unused-import
import tensorflow as tf
# your code
If you import silence_tensorflow
in the context of a function you will get a different warning from pylint: unused variable. You can use the flag disable=unused-variable
as such:
def func():
import silence_tensorflow.auto # pylint: disable=unused-variable
import tensorflow as tf
# your code
This package will set the KMP_AFFINITY
system variable to noverbose
and TF_CPP_MIN_LOG_LEVEL
to level 3
(only errors logged).
If you need a custom value for KMP_AFFINITY
you should reset it after importing the package, as follows:
import os
from silence_tensorflow import silence_tensorflow
backup = os.environ["KMP_AFFINITY"]
silence_tensorflow()
os.environ["KMP_AFFINITY"] = backup
While I really tried to cover all possible logs that TensorFlow can produce, there are some logs that are not silenced by this package. Below you find the ones that we are aware of, alongside the reason why they are not silenced and what you can do to silence them.
TFLite logs are not silenced by this package because they have hardcoded the logging level to INFO
and there is no way to change it from the Python side.
TFLite will cause info logs such as the following to be printed:
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
If you are willing to recompile your own version of TensorFlow Lite, you can change the logging level to ERROR
by changing the line mentioned above or set it in your C++ code as follows, as described in this issue:
tflite::LoggerOptions::SetMinimumLogSeverity(tflite::TFLITE_LOG_SILENT);
This software is distributed under the MIT License.