-
Notifications
You must be signed in to change notification settings - Fork 613
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Create TFA OSS Usage Analyzer #236
Comments
Let me know where I can help. |
@seanpmorgan Hi Sean, is this still active? |
Hey Tzu-Wei. Yeah... still active but not a priority. I don't think we'll be gauging OSS adoption until ~6months after TF2 release. |
Sure, thanks for the clarification 😃 |
@seanpmorgan It is not the contrib project resurrection but I have a quick script to make a rought count of tensorflow_addons repos on github: We have |
I've another stub for an histogram sampling in the first 100 repositories: |
Awesome thanks @bhack this is very useful. We're also interested in what addons have no usage as well to help us determine if there are bugs/implementation problems, duplicated code on different repos, etc. Thanks a bit trickier to do but certainly useful |
What do you mean? |
As in which specific addons modules are / are not being used. |
Yes no usage it is quite hard to define for pattern matching. For this subtopic I am mainly interested in the Google brain/TF perimeters as you know we could to achieve an important policy enforcing goal. It is hard in these days to find refence impl of non Google papers in Tensorflow so at least having Google Research/Brain/TF team itself contributing in addon could help on the points that you have exposed. |
TensorFlow Addons is transitioning to a minimal maintenance and release mode. New features will not be added to this repository. For more information, please see our public messaging on this decision: Please consider sending feature requests / contributions to other repositories in the TF community with a similar charters to TFA: |
We've been using the TF contrib analyzer provided by @kingspp in order to triage components of tf.contrib to be moved to Addons:
https://tf-contrib-analyzer.herokuapp.com/
https://github.com/kingspp/tf-contrib-analyzer
Per our charter... we'll need to analyze the usage of Addons as part of our periodic review process. As part of a fork we may want to add some changes to improve the accuracy and push them upstream. The first one that comes to mind is to ignore
.rst
and.md
files which are more than likely false positives.cc @dynamicwebpaige as this was discussed in the Monthly meeting and there may be interest in setting this up for all of TensorFlow if applicable.
The text was updated successfully, but these errors were encountered: