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Support affine int8 weight specifications in Arm quantization (#24337) - #24337
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/24337
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@AdithyaReddy9 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D128346146. |
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AdrianLundell
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Thanks for the contribution, the change looks good but please add full E2E integration tests to ensure affine weights are supported across the full pipeline, preferably using pytest and the test pipelines used in other tests, and make sure the linter passes.
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…h#24337) Summary: Pull Request resolved: pytorch#24337 Allow static per-tensor and per-channel affine weight specifications. Retain the channel axis when deriving bias quantization parameters. Serialize identical per-channel convolution weight zero points as the scalar required by TOSA and reject conflicting zero points explicitly. Differential Revision: D128346146 Signed-off-by: Adithya Reddy Nallabolu <adithyareddy@meta.com>
Added pytest E2E coverage through quantization, export, TOSA lowering and numerical reference comparison, including nonzero affine weight zero points and bias. All 10 local tests pass |
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Looks like the lintrunner is failing (this happens sometimes with internal diffs exported). Can you fix that? |
rascani
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…h#24337) Summary: Allow static per-tensor and per-channel affine weight specifications. Retain the channel axis when deriving bias quantization parameters. Serialize identical per-channel convolution weight zero points as the scalar required by TOSA and reject conflicting zero points explicitly. Reviewed By: rascani Differential Revision: D128346146
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…h#24337) Summary: Allow static per-tensor and per-channel affine weight specifications. Retain the channel axis when deriving bias quantization parameters. Serialize identical per-channel convolution weight zero points as the scalar required by TOSA and reject conflicting zero points explicitly. Reviewed By: rascani Differential Revision: D128346146
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Summary:
Allow static per-tensor and per-channel affine weight specifications. Retain the channel axis when deriving bias quantization parameters. Serialize identical per-channel convolution weight zero points as the scalar required by TOSA and reject conflicting zero points explicitly.
Reviewed By: rascani
Differential Revision: D128346146