Arm backend: Reorder BN-fusing and decomposition#19276
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oscarandersson8218 merged 1 commit intopytorch:mainfrom May 5, 2026
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Arm backend: Reorder BN-fusing and decomposition#19276oscarandersson8218 merged 1 commit intopytorch:mainfrom
oscarandersson8218 merged 1 commit intopytorch:mainfrom
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19276
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ❌ 2 New Failures, 1 Cancelled Job, 1 Pending, 6 Unrelated FailuresAs of commit 144df55 with merge base 0a113f8 ( NEW FAILURES - The following jobs have failed:
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zingo
approved these changes
May 4, 2026
- Make sure BN-fusing pass is run before decomposition pass as folding is more efficient then decomposition. - Skip FuseBatchNorm2dPass for bf16 batchnorm outputs as folding conv+batchnorm into bf16 conv weights introduces larger numerical error than the unfused path, which caused regressions in bf16 tests. - Add a regression test covering the bf16 non-fusion behavior. - Fix the bias placeholder validation in the pass to check the bias node instead of the weight node. Signed-off-by: Oscar Andersson <oscar.andersson@arm.com> Change-Id: I62b34ab70bfa537bd0ee9fa664433d6ccb279a09
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Make sure BN-fusing pass is run before decomposition pass.
cc @digantdesai @freddan80 @per @zingo @mansnils @Sebastian-Larsson @robell