| |
| |
| """Dump the served model's debug outputs (class map, fp32 margins and logits) for structural A/B bit checks. |
| |
| bin/devrun -t 900 -- env SCENESEG_EPI=1 python -u code/scripts/diag/dump_outputs.py --out a.npz [--input img ...] |
| python code/scripts/diag/dump_outputs.py --compare a.npz b.npz |
| |
| Every knob comes from the environment (``SCENESEG_*``), so one process per configuration. Inputs: the shipped sample |
| and, when present, the PandaSet 019 frame of the workspace. The served (traced) class map and the debug trace's |
| margins / logits are stored per input; ``--compare`` reports bit-identity per array. |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import sys |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
| CODE = Path(__file__).resolve().parents[2] |
| SAMPLE = CODE / "tt_sceneseg" / "samples" / "highway_normal_1.png" |
| PANDASET = (CODE.parents[2] / "research" / "sceneseg" / "public_data" / "shippable" / "pandaset_019_f40_front_camera" |
| / "pandaset_019_f40_front_camera.jpg") |
|
|
|
|
| def compare(a: str, b: str) -> int: |
| x, y = np.load(a), np.load(b) |
| ok = True |
| for k in sorted(set(x) | set(y)): |
| if k not in x or k not in y: |
| print(f"MISSING {k}") |
| ok = False |
| continue |
| u, v = x[k], y[k] |
| same = u.shape == v.shape and np.array_equal(u.view(np.uint8), v.view(np.uint8)) |
| extra = "" |
| if not same and u.shape == v.shape: |
| if u.dtype.kind == "f": |
| d = np.abs(u.astype(np.float64) - v.astype(np.float64)) |
| extra = f" (max abs diff {d.max():.3g}, {int((u != v).sum())} of {u.size} differ)" |
| else: |
| extra = f" ({int((u != v).sum())} of {u.size} differ, agreement {(u == v).mean():.6f})" |
| ok &= same |
| print(f"{'SAME' if same else 'DIFF'} {k} {u.dtype} {u.shape}{extra}") |
| print("ALL IDENTICAL" if ok else "NOT IDENTICAL") |
| return 0 if ok else 1 |
|
|
|
|
| def main() -> int: |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--out") |
| ap.add_argument("--input", action="append") |
| ap.add_argument("--compare", nargs=2) |
| a = ap.parse_args() |
| if a.compare: |
| return compare(*a.compare) |
| from tt_sceneseg import SceneSeg |
|
|
| inputs = [Path(p) for p in (a.input or [str(SAMPLE)] + ([str(PANDASET)] if PANDASET.is_file() else []))] |
| res = {} |
| with SceneSeg.from_pretrained() as m: |
| m.runner.add_debug_variant() |
| m.runner.capture() |
| print("info:", m.extra_info().get("graph"), flush=True) |
| for p in inputs: |
| canvas = m._prepare(str(p))["prepared"].device_input() |
| served = m.runner(canvas) |
| dbg = m.runner.debug(canvas) |
| res[f"{p.stem}.class_map"] = served["class_map"] |
| for k in ("class_map", "margins", "logits"): |
| res[f"{p.stem}.debug.{k}"] = dbg[k] |
| print(f"{p.name}: class counts {np.bincount(served['class_map'].ravel(), minlength=3).tolist()}", flush=True) |
| np.savez_compressed(a.out, **res) |
| print("saved", a.out) |
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| sys.exit(main()) |
|
|
