Fix batch norm folding in prepare_pt2e for multiple conv->BN chains sharing the same conv weights
#2795
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2795
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 95e561e with merge base 72b35bf ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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jerryzh168
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Aug 19, 2025
| @@ -22,6 +22,26 @@ def forward(self, x): | |||
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| class ToyCNNModel(nn.Module): | |||
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nit: better to be more specific I think, like ConvWithSharedWeightInExportedModel
jerryzh168
reviewed
Aug 19, 2025
torchao/quantization/pt2e/utils.py
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| fused_convs_weight_nodes.add(conv_weight_node) | ||
| del fused_convs_weight_nodes |
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nit: probably no need to delete this explicitly
jerryzh168
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Aug 19, 2025
jerryzh168
added
topic: improvement
Fixed, thanks. |
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@subhankarpal has imported this pull request. If you are a Meta employee, you can view this in D80546723. |
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@subhankarpal no need for manual import, our oncall will import this in diff train |
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Summary
For a model with multiple conv->BN chains that have the same conv weights,
prepare_pt2eapplies batch norm folding repeatedly for each chain, causing incorrect conv weights in the output prepared model. This fix ensures batch norm folding is performed only once per unique conv weight set, preventing multiple folds and preserving correct model behavior.Testplan