add read-only capture diagnostic for the 4096-cap parity bug

diag/diagnose_parity_capture.py

@@ -462,30 +462,41 @@ def main() -> None:
     report["row_fresh_raw_vs_behavior"] = stats(
         [abs(a - b) for a, b in zip(fresh_raw, behavior)])
     print("\n== which stored array does each recomputation reproduce? ==")
-    for key in ("padded_vs_row_fresh_T", "padded_fresh_T_vs_behavior",
-                "padded_fresh_T_vs_stored_trainer", "row_fresh_T_vs_behavior",
-                "row_fresh_T_vs_stored_trainer"):
-        if key in report:
-            r_ = report[key]
-        elif key == "row_fresh_T_vs_behavior":
-            r_ = report["guard_fresh_T_vs_behavior"]
-        else:
-            r_ = report["trainer_fresh_T_vs_stored_trainer"]
+    # Tolerant lookup: the guard comparisons are built further down, and an earlier
+    # build of this block indexed them directly and crashed before printing the
+    # engine cross-check (the padded numbers had already printed, so the root cause
+    # was still visible -- but a crash must not truncate the report).
+    for key, alias in (("padded_vs_row_fresh_T", None),
+                       ("padded_fresh_T_vs_behavior", None),
+                       ("padded_fresh_T_vs_stored_trainer", None),
+                       ("row_fresh_T_vs_behavior", "guard_fresh_T_vs_behavior"),
+                       ("row_fresh_T_vs_stored_trainer",
+                        "trainer_fresh_T_vs_stored_trainer")):
+        r_ = report.get(key) or (report.get(alias) if alias else None)
+        if not r_:
+            print(f"  {key:36s} (not available yet in this build)")
+            continue
+        report.setdefault(key, r_)
         print(f"  {key:36s} mean={r_['mean']:.6f} p99={r_['p99']:.4f} "
               f"max={r_['max']:.4f} >0.5={r_['above_0p5']}")
     print("  temperature probe on the TRAINER side (raw reference):")
     for key in ("row_fresh_raw_vs_stored_trainer", "padded_fresh_raw_vs_stored_trainer"):
-        r_ = report[key]
+        r_ = report.get(key)
+        if not r_:
+            continue
         print(f"    {key:34s} mean={r_['mean']:.6f} p99={r_['p99']:.4f} "
               f"max={r_['max']:.4f} >0.5={r_['above_0p5']}")
-    close = {"padded": report["padded_fresh_T_vs_stored_trainer"]["max"],
-             "row": report["trainer_fresh_T_vs_stored_trainer"]["max"]}
-    report["which_recomputation_matches_the_trainer_array"] = (
-        "padded_batch" if close["padded"] < close["row"] / 3 else
-        "per_row" if close["row"] < close["padded"] / 3 else "neither_clearly")
-    print(f"  => the trainer's stored array is reproduced by: "
-          f"{report['which_recomputation_matches_the_trainer_array']}"
-          f"  (padded max={close['padded']:.4f}, row max={close['row']:.4f})")
+    padded_ref = report.get("padded_fresh_T_vs_stored_trainer")
+    row_ref = report.get("row_fresh_T_vs_stored_trainer") or report.get(
+        "trainer_fresh_T_vs_stored_trainer")
+    if padded_ref and row_ref:
+        close = {"padded": padded_ref["max"], "row": row_ref["max"]}
+        report["which_recomputation_matches_the_trainer_array"] = (
+            "padded_batch" if close["padded"] < close["row"] / 3 else
+            "per_row" if close["row"] < close["padded"] / 3 else "neither_clearly")
+        print(f"  => the trainer's stored array is reproduced by: "
+              f"{report['which_recomputation_matches_the_trainer_array']}"
+              f"  (padded max={close['padded']:.4f}, row max={close['row']:.4f})")
     d_raw = [abs(a - b) for a, b in zip(fresh_raw, behavior)]
     d_trainer = [abs(a - b) for a, b in zip(fresh_T, trainer)]
     d_trainer_raw = [abs(a - b) for a, b in zip(fresh_raw, trainer)]