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Arm backend: Support TFA-decomposable INT ops in no-quant mixed profile#20018

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YufengShi-dudu merged 3 commits into
pytorch:mainfrom
YufengShi-dudu:support-tfa-decomposable-int-ops
Jun 4, 2026
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Arm backend: Support TFA-decomposable INT ops in no-quant mixed profile#20018
YufengShi-dudu merged 3 commits into
pytorch:mainfrom
YufengShi-dudu:support-tfa-decomposable-int-ops

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@YufengShi-dudu YufengShi-dudu commented Jun 4, 2026

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In the INT-only profile, some integer ops are expected to be decomposed by the transform-for-annotation pipeline before partitioning, so they are intentionally absent from TOSA_PRO_INT_SupportList.

The no-quant mixed INT+FP profile does not run that pipeline, so the original ops can reach the partitioner and be rejected because they are absent from TOSA_PRO_INT_SupportList. However, these ops can still be supported by decomposition passes in the backend pipeline.

Add a mixed INT support list that extends TOSA_PRO_INT_SupportList with backend-decomposable integer ops for mixed-profile partitioning. Include slice_scatter in that extension and remove the corresponding VGF no-quant xfails

Change-Id: I0ccc5484dc8c8311cefb069df9e2a4878bd98c9a

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani

In the INT-only profile, some integer ops are expected to be
decomposed by the transform-for-annotation pipeline before
partitioning, so they are intentionally absent from
TOSA_PRO_INT_SupportList.

The no-quant mixed INT+FP profile does not run that pipeline, so the
original ops can reach the partitioner and be rejected because they
are absent from TOSA_PRO_INT_SupportList. However, these ops can still
be supported by decomposition passes in the backend pipeline.

Add a mixed INT support list that extends TOSA_PRO_INT_SupportList
with backend-decomposable integer ops for mixed-profile partitioning.
Include slice_scatter in that extension and remove the corresponding
VGF no-quant xfails

Change-Id: I0ccc5484dc8c8311cefb069df9e2a4878bd98c9a
Signed-off-by: Yufeng Shi <yufeng.shi@arm.com>
@YufengShi-dudu YufengShi-dudu requested a review from zingo June 4, 2026 08:50
@YufengShi-dudu YufengShi-dudu added partner: arm For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm ciflow/trunk module: arm Issues related to arm backend release notes: none Do not include this in the release notes labels Jun 4, 2026
@meta-cla meta-cla Bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Jun 4, 2026
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pytorch-bot Bot commented Jun 4, 2026

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🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/20018

Note: Links to docs will display an error until the docs builds have been completed.

❌ 2 New Failures, 1 Cancelled Job, 2 Pending, 1 Unrelated Failure

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@YufengShi-dudu YufengShi-dudu merged commit edd9a6e into pytorch:main Jun 4, 2026
470 of 477 checks passed
Gasoonjia pushed a commit that referenced this pull request Jun 8, 2026
…le (#20018)

In the INT-only profile, some integer ops are expected to be decomposed
by the transform-for-annotation pipeline before partitioning, so they
are intentionally absent from TOSA_PRO_INT_SupportList.

The no-quant mixed INT+FP profile does not run that pipeline, so the
original ops can reach the partitioner and be rejected because they are
absent from TOSA_PRO_INT_SupportList. However, these ops can still be
supported by decomposition passes in the backend pipeline.

Add a mixed INT support list that extends TOSA_PRO_INT_SupportList with
backend-decomposable integer ops for mixed-profile partitioning. Include
slice_scatter in that extension and remove the corresponding VGF
no-quant xfails

Change-Id: I0ccc5484dc8c8311cefb069df9e2a4878bd98c9a


cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils
@Sebastian-Larsson @robell @rascani

Signed-off-by: Yufeng Shi <yufeng.shi@arm.com>
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ciflow/trunk CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. module: arm Issues related to arm backend partner: arm For backend delegation, kernels, demo, etc. from the 3rd-party partner, Arm release notes: none Do not include this in the release notes

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