Disable Tensorflow debugging information

python

logging

tensorflow

best-practices

byAlex Kataev·Oct 6, 2024

To thwart all TensorFlow logging, simply configure the TF_CPP_MIN_LOG_LEVEL environment variable to '3'. Ensure to place these lines initially in your Python script, preceding the Tensorflow import:

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf

This method sanctions a log-free console, providing a clear-cut output.

Level control in TensorFlow 2.x

In the more recent TensorFlow 2.x, managing logging is more streamlined and Pythonic. To curtail verbose output, play with the logging level through TensorFlow's API:

import tensorflow as tf
tf.get_logger().setLevel('ERROR')  # Because 'silence is golden!'

Input this code snippet post importing TensorFlow to allow your console to exhibit only errors.

Extra strategies for a peaceful console

If organic variables and the TensorFlow API don't suffice, the Python's standard logging module comes to your aid to fine-tune the log attention:

import logging
logging.getLogger('tensorflow').setLevel(logging.ERROR)  # Keep calm and code on!

This line suppresses verbose messages, showcasing only error messages from TensorFlow.

Fine-tuning your TensorFlow environment

Dealing with Autograph verbosity

Autograph generating too much noise? TensorFlow comes to the rescue to adjust this:

import tensorflow as tf
tf.autograph.set_verbosity(0)  # Autograph, you now have the right to remain silent.

Ensure Autograph works silently by inputting the above line.

`silence-tensorflow` package

When in need of a simple method such as the silence-tensorflow package, experience an all-in-one solution:

from silence_tensorflow import silence_tensorflow
silence_tensorflow()  # TensorFlow's lullaby.

Invoke immediately post TensorFlow import for a tranquil coding atmosphere.

Streamlining TensorFlow messages

Achieve precision control by filtering TensorFlow outside of Python, e.g., through shell script capabilities:

your_script.py 2>&1 | grep -v "W tensorflow"  # 'Filtering', coming soon to theaters near you!

Execute your Python script piped through grep to filter uncalled-for notices instantly.

Staying updated

Always verify method compatibility with your TensorFlow version before attempting to suppress logs. Remember, in the world of rapid advancement, techniques evolve quickly.

Controlling CUDA/GPU verbosity

Attain better control over GPU-related verbosity by referring to CUDA/GPU TensorFlow documentation for precise environment settings. Especially beneficial for GPU users to manage device allocation messages.