Arm backend: Eliminate one memory copy in executor runner

[perheld]

Prior to this patch, temporary tensors/buffers were used to hold the input data which was then copied over to the actual input tensors for running the inference. This patch removes this copying by instead writing the input data directly to the input tensors.

Change-Id: I20565a67dea8d8070efe9593aff4796c54e5fe90
Signed-off-by: [email protected]

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218

[pytorch-bot]

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❌ 2 New Failures, 1 Unrelated Failure

As of commit 4082ceb with merge base 9f8c2f6 ():

NEW FAILURES - The following jobs have failed:

• trunk / test-arm-cortex-m-size-test (bare_metal) / linux-job (gh)
  RuntimeError: Command docker exec -t d5b5f88373802699807251d705fc45f0663329bd1068aa20c502d7507f299bd2 /exec failed with exit code 1
• trunk / test-models-macos-coreml (w2l) / macos-job (gh)
  The process '/usr/bin/git' failed with exit code 128

BROKEN TRUNK - The following job failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• trunk / test-models-macos-coreml (emformer_transcribe) / macos-job (gh) (trunk failure)
  RuntimeError: Command bash /Users/ec2-user/runner/_work/_temp/exec_script failed with exit code 1

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[perheld]

https://github.com/pytorch/executorch/actions/runs/16622225895/job/47029216900 seems the size has gone above the threshold of 109000 resulting in "Fail 109236 > 109000". I dont know where the threshold value is coming from.

[perheld]

https://github.com/pytorch/executorch/actions/runs/16622225895/job/47029216900 seems the size has gone above the threshold of 109000 resulting in "Fail 109236 > 109000". I dont know where the threshold value is coming from.

Seems the threshold was increased a bit in 69f3da0e332 by @swolchok just a few days ago.

[zingo]

mac os fails also unrelated

[digantdesai]

I dont know where the threshold value is coming from

Arbitrary, this is to keep large, unintended size increases to sneak past without getting noticed. I can bump it again.