feat(hpo): env-var knob overrides + sweep script (18 configs)

- train.py knobs all readable from JEPA_* env vars (JEPA_WINDOW, JEPA_D_MODEL,
  JEPA_DEPTH, etc.) so hpo_sweep.py can override without touching source
- scripts/hpo_sweep.py: 3×2×3 grid over D_MODEL × DEPTH × WINDOW,
  logs to results/hpo/hpo_results.jsonl with leaderboard at end
- 3 new tests: env override correctness, configs() schema validation
- 19/19 tests pass

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

scripts/hpo_sweep.py

@@ -0,0 +1,97 @@
+"""HPO sweep for jepa-fx-risk HEPA backbone.
+
+Runs train.py with different JEPA_* env overrides, logs results to
+results/hpo/hpo_results.jsonl. Each config writes its metrics.json then
+the result is appended to the JSONL.
+
+Usage:
+    python scripts/hpo_sweep.py
+    python scripts/hpo_sweep.py --dry-run   # print configs, don't train
+"""
+import argparse
+import json
+import os
+import subprocess
+import sys
+from datetime import datetime
+from itertools import product
+from pathlib import Path
+
+# ── Search space ──────────────────────────────────────────────────────────────
+SEARCH_SPACE = {
+    "JEPA_D_MODEL": [64, 128, 256],
+    "JEPA_DEPTH":   [2, 4],
+    "JEPA_WINDOW":  [120, 240, 480],
+}
+# Fixed: PATCH_LEN=24 (1-day patches), N_HEADS=4, EPOCHS=300, PHASE1_EPOCHS=200
+
+PYTHON = str(Path(sys.executable))
+OUT_DIR = Path("results/hpo")
+
+
+def configs():
+    """Yield all configs as dicts of JEPA_* env overrides."""
+    keys = list(SEARCH_SPACE.keys())
+    for vals in product(*SEARCH_SPACE.values()):
+        yield dict(zip(keys, vals))
+
+
+def run_config(cfg: dict, metrics_path: str = "metrics.json") -> dict:
+    env = {**os.environ, **{k: str(v) for k, v in cfg.items()}}
+    result = subprocess.run(
+        [PYTHON, "train.py"],
+        env=env,
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        return {"config": cfg, "error": result.stderr[-500:]}
+    stdout_last = result.stdout.strip().split("\n")[-1]
+    with open(metrics_path) as f:
+        m = json.load(f)
+    return {
+        "config": cfg,
+        "val_vol_r2":  m.get("val_vol_r2"),
+        "phase1_r2":   m.get("phase1_r2"),
+        "stdout_last": stdout_last,
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dry-run", action="store_true")
+    args = parser.parse_args()
+
+    OUT_DIR.mkdir(parents=True, exist_ok=True)
+    out_file = OUT_DIR / "hpo_results.jsonl"
+
+    all_cfgs = list(configs())
+    print(f"HPO sweep: {len(all_cfgs)} configs")
+    for i, cfg in enumerate(all_cfgs):
+        label = " ".join(f"{k.replace('JEPA_','')}={v}" for k, v in cfg.items())
+        print(f"\n[{i+1}/{len(all_cfgs)}] {label}")
+        if args.dry_run:
+            continue
+        ts = datetime.utcnow().isoformat()
+        row = run_config(cfg)
+        row["ts"] = ts
+        with open(out_file, "a") as f:
+            f.write(json.dumps(row) + "\n")
+        if "error" in row:
+            print(f"  ERROR: {row['error'][:200]}")
+        else:
+            print(f"  val_vol_r2={row['val_vol_r2']:.4f}  phase1_r2={row['phase1_r2']:.4f}")
+
+    if not args.dry_run:
+        # Print leaderboard
+        rows = [json.loads(l) for l in open(out_file) if l.strip()]
+        rows = [r for r in rows if "error" not in r]
+        rows.sort(key=lambda r: r.get("phase1_r2", -999), reverse=True)
+        print("\n── Leaderboard (by phase1_r2) ─────────────────────────")
+        for r in rows[:5]:
+            cfg_str = " ".join(f"{k.replace('JEPA_','')}={v}" for k,v in r["config"].items())
+            print(f"  {r['phase1_r2']:.4f}  {cfg_str}")
+
+
+if __name__ == "__main__":
+    main()