Arm backend: Add unit tests for per-channel quantization #12192
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Add explicit tests for per-channel quantization to all applicable operators (Convolutions and Linear ops). This is achieved by parametrizing the unit tests such that they both run per-channel and per-tensor quantization. Change-Id: I8b836d1e1d56b13e7046aba651fe401058e2858b
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12192
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (4 Unrelated Failures)As of commit 0c4b4f1 with merge base 29858b4 ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
BROKEN TRUNK - The following jobs failed but was present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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zingo
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failed test fails on other PR and on main also |
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Add explicit tests for per-channel quantization to all applicable operators (Convolutions and Linear ops). This is achieved by parametrizing the unit tests such that they both run per-channel and per-tensor quantization. ### Test plan The unit tests themselves are changed. Thus the code is tested. Co-authored-by: Martin Lindström <[email protected]>
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Add explicit tests for per-channel quantization to all applicable operators (Convolutions and Linear ops). This is achieved by parametrizing the unit tests such that they both run per-channel and per-tensor quantization.
Test plan
The unit tests themselves are changed. Thus the code is tested.
cc @digantdesai @freddan80 @per @zingo @oscarandersson8218