conv-bn folding should be used for CNN-based Vision Models when AMP is used with oneDNN Graph #2535
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…sed with AMP By default, conv-bn folding isn't done with CNN based models when AMP is used with oneDNN Graph. `torch.fx.experimental.optimize.fuse` should be used for such models
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/tutorials/2535
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 812b863 with merge base 3a769b0 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This seems fine, I'm a bit confused by |
msaroufim
approved these changes
Aug 25, 2023
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Thanks for reviewing, @msaroufim! :) |
svekars
reviewed
Aug 25, 2023
Co-authored-by: Svetlana Karslioglu <svekars@meta.com>
svekars
approved these changes
Aug 25, 2023
mikaylagawarecki
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Sep 18, 2023
…s used with oneDNN Graph (pytorch#2535) * Update tuning guide to reflect folding conv-bn when oneDNN Graph is used with AMP By default, conv-bn folding isn't done with CNN based models when AMP is used with oneDNN Graph. `torch.fx.experimental.optimize.fuse` should be used for such models --------- Co-authored-by: Svetlana Karslioglu <svekars@meta.com>
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By default, conv-bn folding isn't done with CNN based models when AMP is used with oneDNN Graph.
torch.fx.experimental.optimize.fuseshould be used for such models