code/scripts
| script | purpose | device |
|---|---|---|
fetch_samples.sh |
downloads the public sample data that is not redistributable (sha256-checked) | no |
bench.py |
stage breakdown of warm forwards on several inputs (API split, host_in / H2D / trace / b2b / D2H, e2e p50 / p99, AICLK, the smoke agreement check; --dispatch / --num-cqs for the D14 matrix, --rig-switch): the card / OPT numbers |
yes, via bin/devrun |
profile_ops.py |
Tracy + device profile: one eager frame with module signposts and --rounds signposted traced replays (python -m tracy -r -p --op-support-count 6000 ...); --graph-report DIR writes a ttnn-visualizer graph report of one eager frame instead |
yes, via bin/devrun |
profile_summary.py |
summary of a profile_ops.py ops CSV: programs, kernel sum, span, op-to-op gaps, per-module / per-op-code tables (eager labels carried to the trace op for op), top ops |
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 |
make_synthetic_sample.py |
the shipped sample samples/synthetic_8cam* (generated, Apache-2.0): render (a ray-cast street seen by a generic METEOR-like rig, preset calib/synthetic_8cam.json), optimise (gradient ascent on the object pixels through the fp32 CPU reference until the 3D heads report the objects with margin), finalise (PNGs, request manifest, the stored CPU-reference /predict body, the feed sha256 golden) |
no (research venv) |
make_sample.py |
builds the PandaSet 019 frame 40 sample (METEOR demo-scene layout, request manifest, preset pandaset_019) from the research ship sample; --dest staging (default: the git-ignored staging_samples_pandaset/, not shipped until the user approves PandaSet samples) or --dest package |
no |
make_goldens.py |
CPU-reference goldens (taps + outputs of 4 frames under research/meteor/goldens/, never shipped), the small decoded golden tests/goldens/pandaset_019_f40_reference.json and the reference body samples/pandaset_019_f40.reference.json of the PandaSet sample (in the staging dir while it is not shipped); cross-checked against the research ONNX Runtime goldens (research venv) |
no |
stress_frames.py |
contained stress of the frame trace (the ETH-dispatch hang investigation): --mode replay / rigs / segrigs; every read bit-compared per rig; --rigs shipped[:N] needs no golden (rigs from the shipped sample: what the container check runs) |
yes, via bin/devrun |
run_public_frames.py |
the served model on the public-dataset frames of research/meteor/public_data (feed sha256 checked), TT outputs written in the CPU-golden layout for compare_tt.py and make_demo.py (development workspace only) |
yes, via bin/devrun |
make_demo.py |
the card's media/ from TT outputs: cards, camera heads and the animation of the public frames (research renderer: privacy blur, attribution footers), the TT-vs-CPU bird's-eye view, the shipped-sample render, media/ATTRIBUTION.md |
no (research venv) |
dump_device_outputs.py, device_stage_check.py, precision_emulation.py, repro_*_eth.py |
port tools: raw device outputs of golden frames, eager stage checks, CPU emulation of precision policies, the standalone ETH-hang repros (PORT_LOG 12.7) | partly |
Everything here ships in code/ on the Hub and inside the image (source.extra_code lists scripts).