Disable Tensorflow debugging information
You can disable all debugging logs using os.environ
:
import osos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import tensorflow as tf
Tested on tf 0.12 and 1.0
In details,
0 = all messages are logged (default behavior)1 = INFO messages are not printed2 = INFO and WARNING messages are not printed3 = INFO, WARNING, and ERROR messages are not printed
2.0 Update (10/8/19)Setting TF_CPP_MIN_LOG_LEVEL
should still work (see below in v0.12+ update), but there is currently an issue open (see issue #31870). If setting TF_CPP_MIN_LOG_LEVEL
does not work for you (again, see below), try doing the following to set the log level:
import tensorflow as tftf.get_logger().setLevel('INFO')
In addition, please see the documentation on tf.autograph.set_verbosity
which sets the verbosity of autograph log messages - for example:
# Can also be set using the AUTOGRAPH_VERBOSITY environment variabletf.autograph.set_verbosity(1)
v0.12+ Update (5/20/17), Working through TF 2.0+:
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 osos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}import tensorflow as tf
You can set this environmental variable in the environment that you run your script in. For example, with bash this can be in the file ~/.bashrc
, /etc/environment
, /etc/profile
, or in the actual shell as:
TF_CPP_MIN_LOG_LEVEL=2 python my_tf_script.py
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 abovetf.logging.set_verbosity(tf.logging.ERROR) # or any {DEBUG, INFO, WARN, ERROR, FATAL}
For 1.14 you will receive warnings if you do not change to use the v1 API as follows:
# append to lines abovetf.compat.v1.logging.set_verbosity(tf.compat.v1.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.
For compatibility with Tensorflow 2.0, you can use tf.get_logger
import loggingtf.get_logger().setLevel(logging.ERROR)