Add constraint to not partition standalone batch norm #1501
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/1501
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit b7089de with merge base 5318baa ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Summary: The XNNPACK backend does not current support lowering standalone (non-fused) batch norms. This will be done in the near future, but models with standalone batch norms are failing to lower as the op is partitioned but cannot be lowered. This change adds a op-level constraint for batch norm to the XNNPACK partitioner to only partition batch norms that can be fused. This constraint will be relaxed once standalone batch norm is fully supported. Differential Revision: D52491544
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Summary: The XNNPACK backend does not current support lowering standalone (non-fused) batch norms. This will be done in the near future, but models with standalone batch norms are failing to lower as the op is partitioned but cannot be lowered. This change adds a op-level constraint for batch norm to the XNNPACK partitioner to only partition batch norms that can be fused. This constraint will be relaxed once standalone batch norm is fully supported. Differential Revision: D52491544
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Summary: The XNNPACK backend does not current support lowering standalone (non-fused) batch norms. This will be done in the near future, but models with standalone batch norms are failing to lower as the op is partitioned but cannot be lowered. This change adds a op-level constraint for batch norm to the XNNPACK partitioner to only partition batch norms that can be fused. This constraint will be relaxed once standalone batch norm is fully supported. Reviewed By: mcr229 Differential Revision: D52491544
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This pull request has been merged in 30732fe. |
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Summary:
The XNNPACK backend does not current support lowering standalone (non-fused) batch norms. This will be done in the near future, but models with standalone batch norms are failing to lower as the op is partitioned but cannot be lowered.
This change adds a op-level constraint for batch norm to the XNNPACK partitioner to only partition batch norms that can be fused. This constraint will be relaxed once standalone batch norm is fully supported.
Differential Revision: D52491544