armdeveloperecosystem/sme-executorch-profiling/validate-workflow

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Run or audit the end-to-end SME2 ExecuTorch profiling smoke test. Use when Codex needs to prove a fresh workspace works, validate setup/build/export/pipeline wiring with toy_cnn, check generated artifacts before a PR or demo, or diagnose which workflow stage is broken.

Install

npx vskill@latest install armdeveloperecosystem/sme-executorch-profiling/validate-workflow

SKILL.md

Validate Workflow

Operating Rules

  • Use the smoke test to validate wiring, not benchmark quality. The toy model is for functional confidence.
  • Run from the repository root.
  • For public validation, use a clean pinned ExecuTorch checkout with no ET/XNNPACK patches. If local-development exceptions are used, report them explicitly.
  • Be precise about validation scope: macOS smoke validation does not require Android NDK; Android validation requires NDK-built Android runners plus a device run when making device-side claims.
  • SME2 kernel-selection proof requires SME2-capable hardware. On macOS this means Apple Silicon with SME2 support; on Android this means an Armv9 SME2-capable device.
  • Keep generated out_toy_cnn/ artifacts unless the user asks for cleanup; they are useful evidence for later diagnosis.
  • If the full smoke test is too expensive for the environment, run the staged validation and report the last completed gate.

Procedure

  1. For macOS smoke validation:

``bash export EXECUTORCH_DIR=/path/to/executorch bash model_profiling/scripts/setup_repo.sh bash model_profiling/scripts/build_runners.sh source .venv/bin/activate python model_profiling/scripts/validate_setup.py --require-xnntrace-runners python model_profiling/scripts/run_quick_test.py python model_profiling/scripts/mac_pipeline.py \ --config model_profiling/configs/toy_cnn_trace_run.json python model_profiling/scripts/validate_results.py \ --results model_profiling/out_toy_cnn/runs/mac_trace \ --require-sme2-kernels ``

  1. For staged macOS validation after setup already exists:

``bash export EXECUTORCH_DIR=/path/to/executorch source .venv/bin/activate python model_profiling/scripts/validate_setup.py --skip-runners bash model_profiling/scripts/build_runners.sh python model_profiling/scripts/validate_setup.py --require-xnntrace-runners python model_profiling/export/export_model.py \ --model toy_cnn \ --dtype fp16 \ --outdir model_profiling/out_toy_cnn/artifacts python model_profiling/scripts/mac_pipeline.py \ --config model_profiling/configs/toy_cnn_run.json python model_profiling/scripts/validate_results.py \ --results model_profiling/out_toy_cnn/runs/mac python model_profiling/scripts/mac_pipeline.py \ --config model_profiling/configs/toy_cnn_trace_run.json python model_profiling/scripts/validate_results.py \ --results model_profiling/out_toy_cnn/runs/mac_trace \ --require-sme2-kernels ``

  1. For Android runner validation after setting ANDROID_NDK or ANDROID_NDK_HOME:

``bash bash model_profiling/scripts/check_prereqs.sh --android-run bash model_profiling/scripts/build_runners.sh source .venv/bin/activate python model_profiling/scripts/validate_setup.py \ --require-xnntrace-runners \ --require-android-runners ``

Android device validation also needs an exported .pte, an Android pipeline config that points at executorch/cmake-out/android-arm64-v9a*/executor_runner, and an authorized adb device. Use android_pipeline.py --remote-device <host:port> only for an ADB-over-network device.

  1. Re-run analysis only if execution completed but analysis outputs are missing:

``bash python model_profiling/scripts/analyze_results.py \ --run-dir model_profiling/out_toy_cnn/runs/mac ``

Success Criteria

  • model_profiling/out_toy_cnn/artifacts/toy_cnn_xnnpack_fp16.pte exists and is non-empty.
  • Timing runners executorch/cmake-out/mac-arm64/executor_runner and executorch/cmake-out/mac-arm64-sme2-off/executor_runner exist.
  • Trace runners executorch/cmake-out/mac-arm64-xnnlog/executor_runner and executorch/cmake-out/mac-arm64-sme2-off-xnnlog/executor_runner exist.
  • For Android validation, Android timing and trace runners exist under executorch/cmake-out/android-arm64-v9a*, and the Android NDK toolchain is available.
  • model_profiling/out_toy_cnn/runs/mac/manifest.json and metrics.json exist.
  • At least one .etdump, one *_all_runs_timeline.csv, and analysis_summary.json exist under model_profiling/out_toy_cnn/runs/mac.
  • model_profiling/out_toy_cnn/runs/mac_trace/*_kernels.csv exists.
  • validate_results.py exits 0 for timing and validate_results.py --require-sme2-kernels exits 0 for trace.

Failure Triage

  • Setup failure: use setup-workspace and stop before build/export.
  • Build failure: use build-runners and preserve CMake logs.
  • Export failure: use export-model and inspect model registry/import errors.
  • Pipeline failure: use run-profiling; validate config paths and runner paths.
  • Analysis failure: use analyze-results; inspect ETDump conversion and .etrecord availability.

Reporting Template

When validation completes, report:

text
Validation result: pass|fail
Last completed stage: setup|build|export|pipeline|analysis|results-validation
Validation scope: macOS smoke|Android runner build|Android device run
Key artifacts:
- <path to .pte>
- <path to run dir>
- <path to trace run dir>
- <path to analysis_summary.json>
Notes:
- <warnings about local ExecuTorch patches, missing optional etrecord, trace logs, or platform limits>

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

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