Add test to check that classification models are FX-compatible #3662
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NicolasHug
approved these changes
Apr 13, 2021
datumbox
approved these changes
Apr 17, 2021
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Give me some more time before merging this, there is still some things I'd like to check / verify before getting this in. |
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@fmassa I took care of merging with master and making this up-to-date with our new testing infra. LMK if I can help move this forward w.r.t. #3662 (comment) ! |
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Thanks @NicolasHug ! Let's get this PR merged. I'm not yet sure if we will be adding as constraint that all classification models will be FX-compatible in the future, but at least having this check here will enable us to think about it if it breaks in the future. |
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Hey @fmassa! You merged this PR, but no labels were added. |
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…le (#3662) Summary: * Add test to check that classification models are FX-compatible * Replace torch.equal with torch.allclose * remove skipling Reviewed By: fmassa Differential Revision: D29264313 fbshipit-source-id: 4e57e255c6ce680fc6deee6a9980a7d189e23597 Co-authored-by: Nicolas Hug <nicolashug@fb.com>
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This let us know if the FX-based approach for feature extraction from #3597 would be able to support all classification models in torchvision.
The current approach for feature extraction only work for a subset of the models, and notably doesn't work for inception-style models.
cc @kazhang @jamesr66a for visibility