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Support exp op in XNNPACK backend #11803

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@leafs1 leafs1 commented Jun 18, 2025

Summary

This PR adds support for the exp operator in ExecuTorch via XNNPACK, enabling optimized execution of torch.exp on the XNNPACK backend. The implementation includes updates to operator configuration, serialization, and runtime handling. The exp operator is now properly registered in the XNNPACK partition config and mapped to XNNPACK's xnn_create_exp_operator API in the compiler.

Test plan

I added a new test class TestExp that is a simple torch model with an exp op. It then asserts that the XNNPACK delegate was called while executing the exp op instead of the torch default exp op.

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pytorch-bot bot commented Jun 18, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/11803

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

✅ You can merge normally! (1 Unrelated Failure)

As of commit 27dce32 with merge base 5136175 (image):

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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@facebook-github-bot facebook-github-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 18, 2025
@leafs1 leafs1 force-pushed the milestone3.2 branch 4 times, most recently from 9a33a39 to 5e418e0 Compare June 18, 2025 23:25
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leafs1 commented Jun 18, 2025

@pytorchbot label "release notes: none"

@pytorch-bot pytorch-bot bot added the release notes: none Do not include this in the release notes label Jun 18, 2025
@leafs1 leafs1 force-pushed the milestone3.2 branch 4 times, most recently from abfe5b8 to 108eaa5 Compare June 18, 2025 23:34
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@leafs1 has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

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