Arm backend: Use FP64 conv in NSS quantized ref - #23259
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Temporarily evaluate reference convolutions in FP64 for the random-data INT test, casting each result back to FP32 to reduce sensitivity to host-dependent bias accumulation. Keep calibration, export, and qtol unchanged. Assert that the reference graph contains all 14 expected convolutions so the FP64 override cannot silently become ineffective. Preserve the existing quantization-stage settings when replacing the stage. Validation: NSS random-data INT test and file-specific lint pass on Ubuntu. Temporary workaround for MLETORCH-2609. Authored with assistance from OpenAI Codex. Signed-off-by: Sangwon Ha <sangwon.ha@arm.com> Change-Id: Ibaed52de6562b0e990a4372d6390349183a7ee51
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/23259
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 2 Pending, 3 Unrelated FailuresAs of commit 07bfe01 with merge base bfdfe10 ( 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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@pytorchbot label 'release notes: none' |
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@pytorchbot label 'partner: arm' |
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We have a lot of errors in this tests here on github (some/all? before this PR) IThis might add 2 new, I think it was 7 before and 9 now. Would be nice to land a fix before pile:ing up to much errors and PRs if we need to revert. |
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Did you got the Arm tests green before merging? |
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Oh I still see you had Bummer. |
Temporarily evaluate reference convolutions in FP64 for the random-data INT test, casting each result back to FP32 to reduce sensitivity to host-dependent bias accumulation. Keep calibration, export, and qtol unchanged.
Assert that the reference graph contains all 14 expected convolutions so the FP64 override cannot silently become ineffective. Preserve the existing quantization-stage settings when replacing the stage.
Validation: NSS random-data INT test and file-specific lint pass on Ubuntu.
Temporary workaround for MLETORCH-2609.
Authored with assistance from OpenAI Codex.
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani