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Qualcomm AI Engine Direct - Support floor_divide with int input in QNN HTP backend #14888
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Qualcomm AI Engine Direct - Support floor_divide with int input in QNN HTP backend #14888
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14888
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 FailuresAs of commit 13d9dae with merge base fb87fa6 ( NEW FAILURES - The following jobs have failed:
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This PR needs a
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…N HTP backend Summary: - Since QNN does not support floor_divide operations for int32 or int64 inputs, it is necessary to decompose the operation into a division using floating-point precision, followed by applying the floor function.
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Hi @cccclai, |
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Thank you!
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@pytorchbot cherry-pick --onto release/1.0 -c regression |
…N HTP backend (#14888) ### Summary - Since QNN does not support floor_divide operations for int32 or int64 inputs, it is necessary to decompose the operation into a division using floating-point precision, followed by applying the floor function. ### Test plan UT added Author: @shewu-quic cc @cccclai @shewu-quic @haowhsu-quic @DannyYuyang-quic @cbilgin --------- Co-authored-by: shewu <shewu@qti.qualcomm.com> (cherry picked from commit 5af73eb)
Cherry picking #14888The cherry pick PR is at #15120 and it is recommended to link a regression cherry pick PR with an issue. The following tracker issues are updated: Details for Dev Infra teamRaised by workflow job |
Summary
Test plan
UT added
Author: @shewu-quic
cc @cccclai @shewu-quic @haowhsu-quic @DannyYuyang-quic @cbilgin