onnx-and-benchmarking

# ONNX and benchmarking Use this sub-skill when the task is about `--onnx`, ONNX conversion, CPU latency, `OMP_NUM_THREADS`, `latency.py`, or `speed_cpu.py`. ## When to read Read this sub-skill when the task asks to: - Use ONNX Runtime instead of the PyTorch model path. - Explain or prepare `TDDFA_ONNX` and `FaceBoxes_ONNX`. - Run end-to-end latency timing on an image. - Run the model-only CPU microbenchmark. - Diagnose missing `.onnx` files, OpenMP/libomp issues, or unstable timings. ## Before running 1. Use `../setup-and-assets/` to build and verify the baseline checkout. 2. Check `../../references/model-assets.md` for which `.pth`, `.pkl`, and generated `.onnx` assets are involved. 3. Keep benchmark inputs and thread counts fixed when comparing numbers. ## Latency wrapper The latency wrapper preserves the original `latency.py` CLI. Put original arguments after `--`: ```bash python <skill-root>/sub-skills/onnx-and-benchmarking/scripts/run-latency.py \ --repo-root <checkout> -- \ -f <image-path> --onnx --repeated 1 --warmup true ``` This reports face detection, 3DMM regression, and reconstruction timing. ## Speed wrapper The speed wrapper preserves `speed_cpu.py`: ```bash python <skill-root>/sub-skills/onnx-and-benchmarking/scripts/run-speed-cpu.py \ --repo-root <checkout> ``` It runs a random input through `weights/mb1_120x120.onnx` and prints the mean and standard deviation per inference. ## ONNX conversion behavior - `FaceBoxes_ONNX` converts `FaceBoxesProd.pth` to `FaceBoxesProd.onnx` if the ONNX file is missing. - `TDDFA_ONNX` converts the selected `.pth` checkpoint and the BFM decoder if the ONNX artifacts are missing. - Conversion is CPU-safe but mutates the checkout by writing generated `.onnx` files. ## Thread and provider notes - The repo sets `OMP_NUM_THREADS=4` in the ONNX demo paths. - `KMP_DUPLICATE_LIB_OK=True` is set by the demo scripts before ONNX imports. - CPU ONNX Runtime is the baseline. CUDA/other providers are outside the required verification scope. - On macOS, the original README notes that `libomp` may be required. ## Troubleshooting Read `references/troubleshooting.md` for ONNX-specific issues and `../../references/troubleshooting.md` for shared setup failures.