Qualcomm AI Engine Direct - Remove AIHub Example Scripts

[winskuo-quic]

Summary

We will remove AIHUB sample code for now as it is hard to maintain since each released version has different IO's for context binary, and it is hard to create a runner for each version.
This PR removes all python, c++, and CMAKE files
We will still keep logic in backends/qualcomm for aihub in case this feature is needed again in the future.

GH stack:

• ->Qualcomm AI Engine Direct - Remove AIHub Example Scripts #19144
• Qualcomm AI Engine Direct - Remove SKILL.md info related to AIHub and README #19143

Test plan

Ensure PR does not break existing internal and external CI

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/19144

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❗ 1 Active SEVs

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• Rolling out OSDC (ARC) runners on pull & trunk workflows in PyTorch main

❌ 3 New Failures, 2 Unrelated Failures

As of commit cdea7fb with merge base bf64fa1 ():

NEW FAILURES - The following jobs have failed:

• Test ARM Backend / test-arm / test-backend-linux (arm_tosa_fp, operators) / linux-job (gh)
  RuntimeError: Command docker exec -t 83038c9948949551832ebe2b72405bc009ef66ebb47f784ff4fdceaaa7abe3ce /exec failed with exit code 92
• Test ARM Backend / test-arm / test-backend-linux (arm_vgf_fp, models) / linux-job (gh)
  RuntimeError: Command docker exec -t 218503908e961033bc6f6b076d041be3c5cb96857c0bc060e4896cda803d5712 /exec failed with exit code 92
• Test CoreML Backend / test-coreml / test-backend-macos (coreml, models) / macos-job (gh)
  RuntimeError: Command bash /Users/ec2-user/runner/_work/_temp/exec_script failed with exit code 1

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

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

• pull / unittest / windows / windows-job (gh) (trunk failure)
  ##[error]The operation was canceled.
• pull / unittest-editable / windows / windows-job (gh) (trunk failure)
  ##[error]The operation was canceled.

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[abhinaykukkadapu]

@winskuo-quic can you give a bit of context when and why this was introduced, why are we thinking to deprecate, i understand that we need to customize the runner per version and model, but i like the idea of something readily available for our users to get started, may be we can think about the optimum-et (qnn recipe) approach?