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Document weight management for KerasCV #71

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LukeWood opened this issue Jan 31, 2022 · 5 comments
Closed

Document weight management for KerasCV #71

LukeWood opened this issue Jan 31, 2022 · 5 comments
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@LukeWood
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This includes:

  • default values
  • code locations
  • GCS upload
  • how to reproduce weights
  • where to store reproduction scripts
@LukeWood LukeWood self-assigned this Jan 31, 2022
@bhack
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bhack commented Jan 31, 2022

Some of this points are really important as they are potentially going to expand over the limited reporducbility of the train process. A topic that wasn't handled in the recent PR review at:
keras-team/keras#15447

@bhack
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bhack commented Jan 31, 2022

Just an extra point, I hope that we could evaluate to have some free CI resource for training job resoruces community integrated with Github Action.
But I know that it could be partially connected to this:
tensorflow/build#61 (comment)

@bhack
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bhack commented Apr 11, 2022

Why we are closing this?

@LukeWood
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Why we are closing this?

Project direction has continued to evolve, and while this is still something we will do, this bug is not actionable at this time.

@bhack
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bhack commented Apr 11, 2022

Ok please put a short sentence when you are closing a ticket if it is not super trivial to understand why we are closing it without participating to the internal meetings. So that we could keep the "external" community on the same page. Thanks

freedomtan pushed a commit to freedomtan/keras-cv that referenced this issue Jul 20, 2023
* add base merge layer

* format docstrings

* add  layer

* add test cases for  layer

* Add import for  layer

* fix build function

* add dynamic and static tests

* fix pytest import

* fix pytest decorator

* remove batch size from dynamic shape test

* fix keras reference

* refactor test class

* fix tf tests, and linting issues

* add subtract layer

* add tests for subtract layer

* fix linting issues

* add average layer

* add maximum layer

* dd minimum layer

* add multiply layer

* add tests for average, minimum, maximum, and multiply layers
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