Arm backend: Unsqueeze rank 0 tensor at vgf runtime #14856
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Rank 0 tensors are not supported in SPV_ARM_tensor. We need to symbolically unsqueeze scalar IOs at runtime. * Remove xfails related to MLETORCH-1410 Signed-off-by: Ryan O'Shea <[email protected]> Change-Id: I1cf46919dec422b15f51faf18d676c661df276a6
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14856
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 1 Unrelated FailureAs of commit 152b4aa with merge base 7d2b8c6 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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A lot of test fails (including Arm tests) Im rebasing to retrigger all tests |
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Fails are unrelated |
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@pytorchbot cherry-pick --onto release/1.0 -c regression |
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Rank 0 tensors are not supported in SPV_ARM_tensor. We need to symbolically unsqueeze scalar IOs at runtime. * Remove xfails related to MLETORCH-1410 Signed-off-by: Ryan O'Shea <[email protected]> (cherry picked from commit 8fbc42c)
Cherry picking #14856The cherry pick PR is at #14934 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 |
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Rank 0 tensors are not supported in SPV_ARM_tensor.
We need to symbolically unsqueeze scalar IOs at runtime.
Change-Id: I1cf46919dec422b15f51faf18d676c661df276a6
cc @freddan80 @per @zingo @oscarandersson8218 @digantdesai