Make building training loop calibration-gated

This commit is contained in:
Jens
2026-07-27 09:29:07 +02:00
parent 8155acf969
commit 1c6cf6a6a8
3 changed files with 168 additions and 28 deletions
+102 -20
View File
@@ -29,6 +29,45 @@ def write_json(path: Path, value: dict[str, Any]) -> None:
temporary.replace(path)
def select_calibration_threshold(report: dict[str, Any]) -> dict[str, Any]:
"""Choose a threshold without consulting test or background evidence."""
eligible = [item for item in report["sweeps"] if item["pure_empty_false_positives"] == 0]
if not eligible:
eligible = report["sweeps"]
return max(
eligible,
key=lambda item: (
min(region["f1"] for region in item["regions"].values()),
item["aggregate"]["f1"],
-item["pure_empty_false_positives"],
),
)
def calibration_failures(
chosen: dict[str, Any],
*,
min_aggregate_f1: float,
min_region_f1: float,
min_region_precision: float,
min_region_recall: float,
max_pure_empty_fp: int,
) -> list[str]:
failures: list[str] = []
if chosen["aggregate"]["f1"] < min_aggregate_f1:
failures.append("calibration_aggregate_f1_below_gate")
for region, values in chosen["regions"].items():
if values["f1"] < min_region_f1:
failures.append(f"calibration_{region}_f1_below_gate")
if values["precision"] < min_region_precision:
failures.append(f"calibration_{region}_precision_below_gate")
if values["recall"] < min_region_recall:
failures.append(f"calibration_{region}_recall_below_gate")
if chosen["pure_empty_false_positives"] > max_pure_empty_fp:
failures.append("calibration_pure_empty_false_positive_gate_failed")
return failures
def training_command(
yolo: str,
*,
@@ -112,6 +151,11 @@ def main() -> int:
parser.add_argument("--translate", type=float, default=0.1)
parser.add_argument("--seed", type=int, default=20260731)
parser.add_argument("--yolo", default="yolo")
parser.add_argument("--min-aggregate-f1", type=float, default=0.55)
parser.add_argument("--min-region-f1", type=float, default=0.45)
parser.add_argument("--min-region-precision", type=float, default=0.5)
parser.add_argument("--min-region-recall", type=float, default=0.4)
parser.add_argument("--max-pure-empty-fp", type=int, default=0)
parser.add_argument("--dry-run", action="store_true")
args = parser.parse_args()
if args.iterations < 1:
@@ -174,11 +218,7 @@ def main() -> int:
shutil.copy2(best, candidate)
reports: dict[str, Path] = {}
for role, summary in (
("calibration", args.calibration_summary),
("test", args.test_summary),
("background", args.background_summary),
):
for role, summary in (("calibration", args.calibration_summary),):
report = iteration_dir / f"{role}.json"
reports[role] = report
run(
@@ -203,22 +243,64 @@ def main() -> int:
iteration_dir / f"{role}.log",
)
assessment = iteration_dir / "assessment.json"
run(
[
sys.executable,
str(scripts_dir / "assess_belgium_building_training_iteration.py"),
"--calibration",
str(reports["calibration"]),
"--test",
str(reports["test"]),
"--background",
str(reports["background"]),
"--output",
str(assessment),
],
iteration_dir / "assessment.log",
allowed={0, 2},
calibration = json.loads(reports["calibration"].read_text(encoding="utf-8"))
chosen = select_calibration_threshold(calibration)
failures = calibration_failures(
chosen,
min_aggregate_f1=args.min_aggregate_f1,
min_region_f1=args.min_region_f1,
min_region_precision=args.min_region_precision,
min_region_recall=args.min_region_recall,
max_pure_empty_fp=args.max_pure_empty_fp,
)
if failures:
write_json(
assessment,
{
"schema_version": 1,
"status": "continue_training_loop",
"phase": "calibration_rejected",
"threshold_selection_source": "calibration_only",
"selected_threshold": chosen["threshold"],
"calibration": chosen,
"test": None,
"background": None,
"failures": failures,
},
)
else:
for role, summary in (
("test", args.test_summary),
("background", args.background_summary),
):
report = iteration_dir / f"{role}.json"
reports[role] = report
run(
[
sys.executable,
str(scripts_dir / "evaluate_belgium_building_candidate.py"),
"--model", str(candidate),
"--summary", str(summary),
"--corpus-manifest", str(args.corpus_manifest),
"--output", str(report),
"--device", "cuda:0",
"--max-det", str(args.max_det),
"--imgsz", str(args.imgsz),
],
iteration_dir / f"{role}.log",
)
run(
[
sys.executable,
str(scripts_dir / "assess_belgium_building_training_iteration.py"),
"--calibration", str(reports["calibration"]),
"--test", str(reports["test"]),
"--background", str(reports["background"]),
"--output", str(assessment),
],
iteration_dir / "assessment.log",
allowed={0, 2},
)
decision = json.loads(assessment.read_text(encoding="utf-8"))
record = {
"iteration": index,