Add a fast path for _clone_dim_order

[GregoryComer]

Summary

Add a direct memcpy fast path for the portable _clone_dim_order op, as it can be a performance bottleneck. I'd like to more aggressively optimize these out of the graph, but this fast path should reduce the perf impact significantly.

Test plan

Existing correctness tests for the _clone_dim_order implementation should cover it.

For performance, I did a quick test with a default dim order (1, 128, 256, 256) element tensor on an x86 server. This is mainly intended as a quick smoke test and not a proper benchmark. I included numbers for both optimized and debug builds. Optimized matters more, but super long debug runs can be painful for development.

[Optimized Build]
Before: 27.9 ms
After: 6.4 ms

[Debug Build]
Before: 5947.01 ms
After: 7.2 ms

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/15815

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❌ 1 New Failure

As of commit 421c6dc with merge base e774b77 ():

NEW FAILURE - The following job has failed:

• pull / test-moshi-linux / linux-job (gh)
  RuntimeError: Command docker exec -t 76ba0d56cd2c18e8e2b8adde386c1a39d7340c44ed31634379e4ff35ca2ba2e2 /exec failed with exit code 1

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[github-actions]

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[meta-codesync]

@GregoryComer has imported this pull request. If you are a Meta employee, you can view this in D86993338.

[GregoryComer]

Note that the moshi failure is pre-existing.

[Gasoonjia]

LGTM!