tf.debugging.enable_traceback_filtering
Stay organized with collections
Save and categorize content based on your preferences.
Enable filtering out TensorFlow-internal frames in exception stack traces.
tf.debugging.enable_traceback_filtering()
Raw TensorFlow stack traces involve many internal frames, which can be
challenging to read through, while not being actionable for end users.
By default, TensorFlow filters internal frames in most exceptions that it
raises, to keep stack traces short, readable, and focused on what's
actionable for end users (their own code).
If you have previously disabled traceback filtering via
tf.debugging.disable_traceback_filtering()
, you can re-enable it via
tf.debugging.enable_traceback_filtering()
.
Raises |
RuntimeError
|
If Python version is not at least 3.7.
|
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]