From bd819d8c556aee7aae0cff03d2154ad16b65a075 Mon Sep 17 00:00:00 2001 From: hyeokjun32 Date: Mon, 18 May 2026 01:07:12 +0900 Subject: [PATCH] docs: sync portfolio validation counts --- docs/portfolio/inferedge_portfolio_submission.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/portfolio/inferedge_portfolio_submission.md b/docs/portfolio/inferedge_portfolio_submission.md index 42132cb..95fbe98 100644 --- a/docs/portfolio/inferedge_portfolio_submission.md +++ b/docs/portfolio/inferedge_portfolio_submission.md @@ -111,11 +111,11 @@ Run evidence registry / comparability checker. Edge AI inference benchmark resul Recent validation evidence: -- InferEdgeLab: `poetry run python3 -m pytest -q` -> 262 passed -- InferEdgeForge: `python -m pytest -q` -> 89 passed +- InferEdgeLab: `poetry run python3 -m pytest -q` -> 300 passed +- InferEdgeForge: `poetry run pytest -q` -> 92 passed - InferEdgeRuntime: `python3 tests/test_lab_worker_adapter_contract.py` -> 12 tests passed - InferEdgeRuntime: `scripts/smoke_default.sh` -> success -- InferEdgeAIGuard: `python -m pytest -q` -> 110 passed +- InferEdgeAIGuard: `python -m pytest -q -p no:cacheprovider` -> 139 passed - GitHub Actions: Lab Benchmarks success, Runtime CI success - Lab PR #171 기준 1-page architecture summary 문서화 완료 - Lab -> Runtime manual smoke using `yolov8n.onnx`: `/api/analyze` created job `job_9e2321179256`, Lab invoked the C++ Runtime CLI through the dev-only subprocess path, ONNX Runtime executed the model successfully, and the latency/provenance JSON was ingested back into the Lab job result. The smoke reported ONNX Runtime backend available, benchmark status success, mean latency about 47.97 ms, p50 about 46.95 ms, p95/p99 about 51.80 ms, and about 20.85 FPS.