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RFC: Creating SIG Models #314

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merged 2 commits into from
Nov 12, 2020
Merged

RFC: Creating SIG Models #314

merged 2 commits into from
Nov 12, 2020

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jaeyounkim
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@jaeyounkim jaeyounkim commented Oct 23, 2020

This RFC will be open for comment until Wednesday, November 11st, 2020.

Creating SIG Models

We propose to create a TensorFlow SIG Models.

Status Accepted
RFC # 314
Author(s) Jaeyoun Kim (jaeyounkim@google.com), Jing Li (jingli@google.com), Mike Liang (mliang@google.com), Shuangfeng Li (shuangfeng@google.com)
Sponsor Thea Lamkin (thealamkin@google.com)
Updated 2020-10-23

What is this group for?

This group is for discussions and collaborations on enabling community
contributions to TensorFlow Model Garden
and Tensorflow Hub.

SIG Models will focus on empowering the community to contribute state-of-the-art
model implementation in TensorFlow 2. It will benefit the whole community by
providing recommended implementations and models with reproducible results.

SIG Models will have several subgroups (e.g., SIG Models Vision and SIG Models
NLP) covering different machine learning areas. There are several SIG leads for
each group to coordinate the contributions, run community events like contests,
and maintain the code quality through the review process.

@google-cla google-cla bot added the cla: yes label Oct 23, 2020
@theadactyl theadactyl changed the title Creating SIG Models RFC: Creating SIG Models Oct 23, 2020
@theadactyl theadactyl added the RFC: Proposed RFC Design Document label Oct 23, 2020
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sub-mod commented Oct 23, 2020

I would like to be part of the SIG.Thanks

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@perfinion perfinion left a comment

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One thing that is missing from this RFC is a set of guidelines about quality of models in the repo.
SIG-Addons has a good workflow to use as reference. There needs to be a clear statement on quality of the models in the repo and keeping up with maintenance and evolving best-practices. A big risk for a SIG like this is drive-by models that bitrot over time. There must be a process to remove models if they are not up to the standards.

and maintain the code quality through the review process. Each group has the
flexibility to operate differently.

SIG is also a place for community discussions and sharing best practices of
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s/SIG/SIG Models/

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@perfinion I've changed it to SIG Models. Thank you!

([models@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/models)),
arrange a regular (e.g., monthly) video conference call rotated by the SIG
leads. We will also use a Gitter chat channel
(https://gitter.im/tensorflow/models) for discussions.
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This should be gitter.im/tensorflow/sig-models for consistency with the other sig channels, the existing ones are eg gitter.im/tensorflow/sig-build or gitter.im/tensorflow/sig-addons

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@perfinion I've changed it. Thank you for your comment.

the contest
* Review initial submissions and provide more support for selected high-quality
submissions
* Review final submissions and announce results
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what is the lifecycle of such models? I can see at least: draft, initial, final
Any guarantees of maintainability? Can models be deprecated over time?

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We are also trying to figure if a bot could do some keep-alive/MIA checks tensorflow/addons#2024

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The real question is also how to implement something like tensorflow/addons#236. I don't know if this new SIG will have the resource to implement something like to solve this open topic. I think it would be really useful for all the SIGs but also for the TF ecosystem.

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@lc0 The lifecycle of community models will be one of the topics the SIG Models will discuss. We expect that we will also have a periodic review for models. Thank you for your comment.

@bhack Thank you for your suggestion. I agree with you that it would be useful to have such an analyzer. We will definitely discuss it once the TF SIG Models is created. We will ask for more inputs from you.

submissions
* Review final submissions and announce results

## What modes of communication do you intend to use?
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I think would be helpful to also define what is expected use-case.

Do we see it as python module, that can be imported downstream, hence models are tested and maintained.
Or just a collection of scripts, that contributed by different people at different times?

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This comment is connected to the models's reusable components topic.
Some times ago we had a ticket about this at #223

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There are many dups or semi-dups like tensorflow/addons#1903 (comment) that confuse users and third party SIG maintainers.

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@lc0 @bhank Thank you for your suggestions and comments. We will add that as one of the first topics for open discussion after the SIG Models created. We want to start with a small scope and expand it later based on community inputs.

using TensorFlow 2 for state-of-the-art research. Furthermore, SIG provides
product feedback to help TensorFlow to be improved.

## Who will be part of it?
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What about keras-cv/keras-nlp?

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Same question.

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@bhack @AakashKumarNain Yes, the Keras team (keras-cv/nlp) will contribute to the SIG Models.

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bhack commented Oct 26, 2020

In general I think that is great and strategic to have this SIG cause Models and Hub are really one of the unique places in the ecosystem where all of the pieces converges together to compose our end2end goal. Also we often suffer more then the Pytorch ecosystem about availability of third party papers official (and unofficial) reference implementations in the github "universe".

But we really need to take this SIG as an occasion to improve our ecosystem about component re-usability and ownership disambiguation.
It could be nice to have a short grace period for the new components (layer, loss, optimizer, preprocessing, postprocessing, etc.) that would be introduced in TF model.
As we know external members don't know the public roadmap of the different internal teams (and this could happen also between different internal teams) you can find a recap thread at #29.
This could create duplicates, unaware supersedes, implementation divergences and so on.. In Addons we have tried to Draft an early ecosystem-review process to notify the ecosystem that probably could be standardized and improved for general use to improve the coherence between internal teams and external members.
By this point of view I see this SIG one of the most critical points to achieve this goal in our ecosystem.

* Change SIG to SIG Models
* Update the Gitter chat URL (https://gitter.im/tensorflow/sig-models)
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lgtm

@theadactyl theadactyl merged commit 0316251 into tensorflow:master Nov 12, 2020
@theadactyl theadactyl added RFC: Accepted RFC Design Document: Accepted by Review and removed RFC: Proposed RFC Design Document labels Nov 12, 2020
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7 participants