XNNPACK: Run recommended pre-partition transforms in AOT flow#20446
XNNPACK: Run recommended pre-partition transforms in AOT flow#20446mansnils wants to merge 1 commit into
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Wire get_transform_passes() into the XNNPACK example AOT compiler so official exports run the same recommended pre-partition graph transforms used by tests. Update XNNPACK docs and README snippets to show the optional transform_passes stage and clarify that it is recommended in general for XNNPACK before partitioning. Signed-off-by: Måns Nilsson <mans.nilsson@arm.com> Change-Id: I0412c13d9a067a44b3d044d27409157095a4d764
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20446
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: ❌ 4 New Failures, 4 Unrelated FailuresAs of commit f0f41be with merge base 82a605d ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Pull request overview
Wires XNNPACK’s recommended pre-partition graph transform passes into the XNNPACK example AOT export flow, and updates user-facing docs/snippets so “official” exports follow the same recommended lowering pipeline as tests prior to partitioning/delegation.
Changes:
- Run
get_transform_passes()viatransform_passes=...in the XNNPACK exampleto_edge_transform_and_lower(...)call. - Update XNNPACK docs/READMEs to show and recommend the optional pre-partition transform stage for better pattern exposure to the partitioner.
- Add an additional copyright header line in the XNNPACK example AOT compiler script.
Reviewed changes
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Show a summary per file
| File | Description |
|---|---|
| examples/xnnpack/README.md | Documents that the example compiler runs the recommended pre-partition transform stage. |
| examples/xnnpack/aot_compiler.py | Applies get_transform_passes() in the AOT lowering call before XNNPACK partitioning. |
| docs/source/backends/xnnpack/xnnpack-quantization.md | Updates lowering snippet to include transform_passes and explains why it’s recommended for XNNPACK. |
| docs/source/backends/xnnpack/xnnpack-overview.md | Updates lowering snippet to include transform_passes and explains why it’s recommended for XNNPACK. |
| backends/xnnpack/README.md | Updates the “manual” lowering snippet to run edge.transform(get_transform_passes()) before partitioning. |
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@claude review this PR |
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Claude finished @mansnils's task in 1m 37s —— View job PR Review: XNNPACK pre-partition transforms in AOT flow
I reviewed the diff against Correctness ✅
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CI noteThe reported new failures appear to be infra/docker-related ( |
Wire get_transform_passes() into the XNNPACK example AOT compiler so official exports run the same recommended pre-partition graph transforms used by tests.
Update XNNPACK docs and README snippets to show the optional transform_passes stage and clarify that it is recommended in general for XNNPACK before partitioning.
cc @GregoryComer @digantdesai @cbilgin @freddan80 @per @zingo @oscarandersson8218 @Sebastian-Larsson @robell @rascani