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bhack opened this issue Nov 6, 2024 · 6 comments
Open

Expand AOTI tutorial to cover AMP #3152

bhack opened this issue Nov 6, 2024 · 6 comments
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@bhack
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bhack commented Nov 6, 2024

📚 The doc issue

I think it would useful to expand AOTI tutorial to cover AMP trained models.

https://pytorch.org/tutorials/recipes/torch_export_aoti_python.html

Suggest a potential alternative/fix

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cc @svekars @brycebortree @sekyondaMeta @ezyang @chauhang @penguinwu @avikchaudhuri @gmagogsfm @zhxchen17 @tugsbayasgalan @angelayi @suo @ydwu4 @desertfire @chenyang78

@bhack
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bhack commented Nov 6, 2024

/cc @agunapal @angelayi @svekars

@agunapal
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agunapal commented Nov 6, 2024

@bhack Thanks for the suggestion. Will check

@bdhirsh bdhirsh added the triaged Issues has been triaged label Nov 8, 2024
@svekars
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svekars commented Nov 8, 2024

Let's move this to the tutorials repo.

@svekars svekars transferred this issue from pytorch/pytorch Nov 8, 2024
@bhack
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bhack commented Jan 31, 2025

What is the status of this with 2.6.0 ?

@angelayi
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@bhack what sort of model are you looking at? Could you provide a pointer?
I would think that an AMP trained model behaves the same as just any model that you pass to export?

@bhack
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bhack commented Apr 16, 2025

Nothing specific just a general guide how to export/aoti compile an amp model.
Mainly not only specifically amp trained but also the case when we want to use amp at inference.

E.g. do we need to amp wrap the model before export/compile? Etc..

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