Silence TensorFlow

Python package to shut up TensorFlow warnings and logs, letting you focus on the important errors.

How do I install this package?

As usual, just download it using pip:

pip install silence_tensorflow

How do I use it?

You only need to import the package before importing TensorFlow:

from silence_tensorflow import silence_tensorflow
silence_tensorflow()
import tensorflow as tf

# your code

Setting the logging level

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")

Can it be done within the import?

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

How can I get pylint to ignore the unused import?

You can use the flag disable=unused-import as such:

import silence_tensorflow.auto  # pylint: disable=unused-import
import tensorflow as tf

# your code

How can I get pylint to ignore the unused variable?

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

How does this work under the hood?

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

Known limitations

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.

TensorFlow Lite (TFLite)

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);

License

This software is distributed under the MIT License.