Fwd: [RFC] Modular TensorFlow

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Bairen YI

Mar 12, 2019, 6:50:50 PM3/12/19
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Hi folks,

We talked about the larger effort to modularize TensorFlow core and how this could affect the networking plugins in our last meeting. Unfortunately, I did not do a great job explaining what is the situation and why we have stuck into the API for the plugin talking to TF core. Now I’m glad we have this RFC from TF team; though it might take a long time for the team to refactor TF core, the networking plugins will benefit from a greater flexibility and less code duplication from this effort.

I encourage all of you in the networking SIG to take a look and make comments to this RFC and its design doc.


Begin forwarded message:

From: "'Edd Wilder-James' via TensorFlow Developers" <devel...@tensorflow.org>
Date: 13 March 2019 at 05:16:58 GMT+8
To: TensorFlow Developers <devel...@tensorflow.org>
Subject: [RFC] Modular TensorFlow
Reply-To: Edd Wilder-James <e...@google.com>

Hi folks,

I'm happy to announce the publication of a new RFCModular TensorFlow, which is now available for comment.

The feedback phase will be open until 2019-03-26. Comments are invited to the pull request linked. You can view the design doc from the PR, and also leave comments inline on the document source.


This project aims to split the TensorFlow codebase into smaller, more focused, repositories that can be released and managed separately. These modules will talk to each other using well defined APIs that guarantee backwards compatibility. Thanks to the module APIs, these modules are now managed/owned/released independently.

thanks in advance for your feedback!

Edd Wilder-James, Open Source Strategy at Google
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