Cortex-M: add a contiguous-layout pad operator - #22028
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/22028
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 10 Unrelated Failures, 1 Unclassified FailureAs of commit ea98643 with merge base 8b93850 ( NEW FAILURES - The following jobs have failed:
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This was referenced Aug 21, 2026
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Add cortex_m::pad_contiguous beside the existing pad. The two differ only in
whether the kernel has to work out the layout for itself: the existing operator
infers it, while this one requires the dim order to say the tensor is contiguous
and then indexes the padding by logical axis.
Not named after an axis order, because padding does not interpret axes the way
convolution and pooling do -- it pads whatever it is told to. What distinguishes
this entry point is that it never guesses. It accepts ranks one to four for the
same reason, so it can replace the inferring operator outright once serialized
programs no longer need that one, rather than sitting beside it forever.
Leave the existing operator alone. Its layout predicate is tolerant on purpose:
the tolerance short-circuits before the dim order is consulted, which is what
keeps it agreeing with the AOT pass for shapes whose serialized dim order cannot
name the channel axis. Two regression cases cover that, since every pre-existing
channels-last pad test used more than one channel and so missed it.
Local Corstone-300 run of the full Cortex-M suite and lintrunner.
Authored with Codex.