update 3-19

2026-03-19 11:18:58 +01:00
parent 7ea85d5426
commit 786457b30d
35 changed files with 4019 additions and 258 deletions
@@ -0,0 +1,107 @@
+#!/usr/bin/env python3
+"""
+10× repeated 5-fold CV runner for the best hypertower configuration
+(nocrop, ensemble mode, both binary and multiclass).
+
+Each repetition uses a different fold-seed so the 5 folds are split
+differently, giving 50 folds per eval-mode total.  Holdout composition
+is kept identical across repetitions (same --holdout-seed).
+
+Results land under:
+    {output-root}/rep{N:02d}/{eval_mode}/ensemble/fold{K}/
+
+Usage
+-----
+    python scripts/main/v2/run_10x5cv.py \
+        --n-reps 10 \
+        --eval-modes binary multiclass \
+        --output-root analysis_data/pipeline_10x5 \
+        --epochs 40 --fused-head \
+        --backbone refugelike
+
+Any extra flags are forwarded directly to V2HyperTower.
+"""
+from __future__ import annotations
+
+import argparse
+import sys
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).resolve().parents[3]
+if str(REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(REPO_ROOT))
+
+from classes.v2.v2_hypertower import V2HyperTower
+
+# Base fold seed for rep 0; rep N uses BASE_SEED + N * SEED_STRIDE
+_BASE_SEED   = 100
+_SEED_STRIDE = 100
+
+
+def _parse_own(argv=None):
+    ap = argparse.ArgumentParser(
+        description=__doc__,
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        add_help=False,
+    )
+    ap.add_argument("--n-reps", type=int, default=10,
+                    help="Number of repetitions (default: 10).")
+    ap.add_argument("--eval-modes", nargs="+",
+                    choices=["binary", "multiclass"],
+                    default=["binary", "multiclass"])
+    ap.add_argument("--output-root", default="analysis_data/pipeline_10x5",
+                    help="Parent directory for all rep sub-runs.")
+    ap.add_argument("-h", "--help", action="store_true")
+    return ap.parse_known_args(argv)
+
+
+def main(argv=None):
+    own, remaining = _parse_own(argv)
+
+    if own.help:
+        print(__doc__)
+        base_parser = V2HyperTower.build_parser()
+        base_parser.print_help()
+        return
+
+    base_parser = V2HyperTower.build_parser()
+    output_root = Path(own.output_root)
+    first_run   = True
+
+    for rep in range(own.n_reps):
+        fold_seed = _BASE_SEED + rep * _SEED_STRIDE
+        rep_label = f"rep{rep:02d}"
+
+        for eval_mode in own.eval_modes:
+            tower_mode = "ensemble"
+
+            # Skip if already fully complete
+            tm_dir = output_root / rep_label / eval_mode / tower_mode
+            if (tm_dir / "summary.json").exists():
+                print(f"[10x5cv] {rep_label} {eval_mode}:{tower_mode} — already done, skipping.")
+                first_run = False
+                continue
+
+            cli = list(remaining) + [
+                "--eval-mode",    eval_mode,
+                "--tower-mode",   tower_mode,
+                "--fold-seed",    str(fold_seed),
+                "--run-name",     rep_label,
+                "--output-root",  str(output_root),
+            ]
+
+            # Reuse crop cache across runs after the first
+            if not first_run:
+                cli.append("--persist-img-crop-cache")
+
+            print(f"\n[10x5cv] Starting {rep_label} {eval_mode}:{tower_mode}  "
+                  f"(fold_seed={fold_seed})")
+            args = base_parser.parse_args(cli)
+            V2HyperTower(args).run()
+            first_run = False
+
+    print(f"\n[10x5cv] All done.  Results in: {output_root}")
+
+
+if __name__ == "__main__":
+    main()