Gate completed checkpoints through training loop

scripts/run_belgium_building_training_loop.py

@@ -191,6 +191,11 @@ def main() -> int:
     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")
+    parser.add_argument(
+        "--evaluate-initial-model",
+        action="store_true",
+        help="Gate an already trained initial checkpoint before starting the next training iteration.",
+    )
     args = parser.parse_args()
     if args.iterations < 1:
         raise SystemExit("--iterations must be positive")
@@ -223,7 +228,8 @@ def main() -> int:
         name = f"iteration-{index:03d}"
         iteration_dir = args.output_dir / name
         train_run = args.output_dir / "runs" / name
-        command = training_command(
+        evaluate_existing = args.evaluate_initial_model and offset == 0 and not state["iterations"]
+        command = None if evaluate_existing else training_command(
             args.yolo,
             model=model,
             data=train_yaml,
@@ -242,12 +248,18 @@ def main() -> int:
             translate=args.translate,
         )
         if args.dry_run:
-            print(json.dumps({"training_command": command}, indent=2))
+            print(json.dumps({"training_command": command, "evaluate_existing": evaluate_existing}, indent=2))
             return 0
-        run(command, iteration_dir / "training.log")
-        best = train_run / "weights" / "best.pt"
-        if not best.is_file():
-            raise RuntimeError(f"Training produced no best checkpoint: {best}")
+        if evaluate_existing:
+            best = model
+            if not best.is_file():
+                raise RuntimeError(f"Initial checkpoint does not exist: {best}")
+        else:
+            assert command is not None
+            run(command, iteration_dir / "training.log")
+            best = train_run / "weights" / "best.pt"
+            if not best.is_file():
+                raise RuntimeError(f"Training produced no best checkpoint: {best}")
         candidate = iteration_dir / "candidate.pt"
         shutil.copy2(best, candidate)
 
@@ -347,6 +359,7 @@ def main() -> int:
             "iteration": index,
             "candidate": str(candidate),
             "candidate_sha256": sha256(candidate),
+            "training_skipped_for_existing_checkpoint": evaluate_existing,
             "assessment": str(assessment),
             "status": decision["status"],
             "failures": decision["failures"],