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@winskuo-quic winskuo-quic commented Oct 7, 2025

Summary

Support following OPs

  • Threshold OP
  • negative dims permute
  • sqrt unit test modified to use desired input rather than random values
  • rsqrt unit test modified to use desired input rather than random values
  • per channel conv3d support

For the sqrt/rsqrt, I believe the sample input for each UT is using rand instead of randn on purpose to prevent negative numbers input, however, if we don't set generate_random_test_inputs=False, then later on it will be using random values consisting of negative numbers, causing nan showing up on output.

If everything works as expected, we should pass 6 more tests, bringing pass rate from 90.7% -> 91.5%

Test plan

UT added

cc @cccclai @shewu-quic @haowhsu-quic @DannyYuyang-quic @cbilgin

@winskuo-quic winskuo-quic requested a review from cccclai as a code owner October 7, 2025 09:48
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pytorch-bot bot commented Oct 7, 2025

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14848

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@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 Oct 7, 2025
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Hi @cccclai,
This PR should support about 5 to 6 more QNN Suite tests. Please have a look. Thanks,

Hi @GregoryComer,
I am working on supporting more QNN operations to pass the suite operator tests. I have made some changes to the suite operator test files. Please let me know if the changes look fine to you. Thanks!

@mergennachin mergennachin added the partner: qualcomm For backend delegation, kernels, demo, etc. from the 3rd-party partner, Qualcomm label Oct 7, 2025
# 1D tensor
self._test_op(RsqrtModel(), (torch.rand(20) + 0.01,), flow)

self._test_op(
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@GregoryComer does the changes in backends/test/suite/operators/* look good to you?

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Hi @cccclai, This PR should support about 5 to 6 more QNN Suite tests. Please have a look. Thanks,

Hi @GregoryComer, I am working on supporting more QNN operations to pass the suite operator tests. I have made some changes to the suite operator test files. Please let me know if the changes look fine to you. Thanks!

Looks good to me. Thanks for catching this and making these updates.

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The changes under qualcomm/* looks good. @GregoryComer please review the changes in the test/suite

@cccclai cccclai merged commit 0e74a17 into pytorch:main Oct 7, 2025
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cccclai commented Oct 7, 2025

@pytorchbot cherry-pick --onto release/1.0 -c regression

pytorchbot pushed a commit that referenced this pull request Oct 7, 2025
### Summary

Support following OPs

- Threshold OP
- negative dims permute
- sqrt unit test modified to use desired input rather than random values
- rsqrt unit test modified to use desired input rather than random
values
- per channel conv3d support

For the sqrt/rsqrt, I believe the sample input for each UT is using
`rand` instead of `randn` on purpose to prevent negative numbers input,
however, if we don't set `generate_random_test_inputs=False`, then later
on it will be using random values consisting of negative numbers,
causing `nan` showing up on output.

If everything works as expected, we should pass 6 more tests, bringing
pass rate from **90.7% -> 91.5%**

### Test plan
UT added

cc @cccclai @shewu-quic @haowhsu-quic @DannyYuyang-quic @cbilgin

(cherry picked from commit 0e74a17)
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Cherry picking #14848

The cherry pick PR is at #14869 and it is recommended to link a regression cherry pick PR with an issue. The following tracker issues are updated:

Details for Dev Infra team Raised by workflow job

GregoryComer pushed a commit that referenced this pull request Oct 8, 2025
### Summary

Support following OPs

- Threshold OP
- negative dims permute
- sqrt unit test modified to use desired input rather than random values
- rsqrt unit test modified to use desired input rather than random
values
- per channel conv3d support

For the sqrt/rsqrt, I believe the sample input for each UT is using
`rand` instead of `randn` on purpose to prevent negative numbers input,
however, if we don't set `generate_random_test_inputs=False`, then later
on it will be using random values consisting of negative numbers,
causing `nan` showing up on output.

If everything works as expected, we should pass 6 more tests, bringing
pass rate from **90.7% -> 91.5%**

### Test plan
UT added

cc @cccclai @shewu-quic @haowhsu-quic @DannyYuyang-quic @cbilgin

(cherry picked from commit 0e74a17)
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