code/scripts
| script | purpose | device |
|---|---|---|
bench.py |
stage breakdown of warm plans (load / host_pre / pack / host_in / H2D / trace / D2H / host_post / e2e / b2b, p50 / p99 / min, AICLK) on one or more scene .npz files, --dispatch / --num-cqs for the dispatch / CQ matrix (the card and OPT_BASELINE.md numbers) |
yes, via bin/devrun |
profile_ops.py |
one eager plan (stage m: and layer-kind c: signposts) + one traced replay between signposts under the device profiler (python -m tracy -r -p -v --op-support-count 16000 ...: a plan is 6,282 programs, over the default 1,000-program buffer) |
yes |
bringup_device.py, precision_exp.py, split_error.py |
the port's numerics experiments (module PCC per configuration, LayerNorm / split-matmul / attention variants, where the plan error of a scene comes from: device encoder vs device decoder); their logs and findings are in PORT_LOG.md (workspace) |
yes |
ref_golden.py |
goldens of the fp32 CPU reference (per-module taps, final outputs, the stored /predict references next to the samples) for the device tests; research venv (onnxruntime): tools/research-venv/bin/python code/scripts/ref_golden.py |
no |
container_smoke.sh |
serve ONE serve profile of the built package (--profile NAME; default profile otherwise), run server/smoke_test.py against it (asserts ETH dispatch, the 12x10 grid and the profile's pins; compares with the stored CPU reference), keep the evidence (container log, /info, the /predict output and the result, in logs/smoke/ of the repo or --log-dir DIR), always stop it; one bin/devrun -t 3600 -k 150 window per profile |
yes |
fetch_samples.sh |
downloads public sample data that may not be redistributed (sha256-checked); diffusion-planner-p150 has none to fetch: both shipped samples are Apache-2.0, and the nuScenes-derived planning instants of the accuracy tables live in the tt-models workspace only | no |
Everything here ships in code/ on the Hub and inside the image (source.extra_code lists scripts).
The card's demo media (media/) were rendered from p150 outputs by workspace scripts that are not shipped, because
most of the data they read (nuScenes) may not be redistributed (media/ATTRIBUTION.md). examples/quickstart.py
writes a simple render (quickstart_bev.png: the input tensors and the plan, bird's-eye view) for any scene .npz.