armdeveloperecosystem/sme-executorch-profiling/validate-workflow
Claude Code and agent skill by armdeveloperecosystem/sme-executorch-profiling
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Checking that the SKILL.md file is still in the repository.
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-workflowSKILL.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
- 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 ``
- 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 ``
- For Android runner validation after setting
ANDROID_NDKorANDROID_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.
- 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.pteexists and is non-empty.- Timing runners
executorch/cmake-out/mac-arm64/executor_runnerandexecutorch/cmake-out/mac-arm64-sme2-off/executor_runnerexist. - Trace runners
executorch/cmake-out/mac-arm64-xnnlog/executor_runnerandexecutorch/cmake-out/mac-arm64-sme2-off-xnnlog/executor_runnerexist. - 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.jsonandmetrics.jsonexist.- At least one
.etdump, one*_all_runs_timeline.csv, andanalysis_summary.jsonexist undermodel_profiling/out_toy_cnn/runs/mac. model_profiling/out_toy_cnn/runs/mac_trace/*_kernels.csvexists.validate_results.pyexits 0 for timing andvalidate_results.py --require-sme2-kernelsexits 0 for trace.
Failure Triage
- Setup failure: use
setup-workspaceand stop before build/export. - Build failure: use
build-runnersand preserve CMake logs. - Export failure: use
export-modeland 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.etrecordavailability.
Reporting Template
When validation completes, report:
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.
Source
- SKILL.md in the repositoryCheckingagent_skill_ml_profiling/validate-workflow/SKILL.md
Popularity
- Repository stars
- 5
- Repository forks
- 2
- 7-day trend score
- 0
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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