File size: 4,980 Bytes
3236af9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | #!/usr/bin/env python3
import argparse
import json
from pathlib import Path
from typing import Any
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
description="Summarize matched Iconoclast vs Heretic benchmark runs."
)
parser.add_argument(
"--spec",
action="append",
required=True,
help=(
"Benchmark spec in the form "
"'label|iconoclast_checkpoint_or_summary|heretic_checkpoint'. "
"Can be passed multiple times."
),
)
parser.add_argument(
"--format",
choices=("markdown", "json"),
default="markdown",
)
return parser.parse_args()
def load_iconoclast_best(path: Path) -> dict[str, Any]:
if path.name == "batch_summary.json":
summary = json.loads(path.read_text())
trials = summary.get("pareto_trials", [])
if not trials:
raise ValueError(f"No pareto trials found in {path}")
return trials[0]
return load_best_from_study(path)
def load_best_from_study(path: Path) -> dict[str, Any]:
trials: dict[int, dict[str, Any]] = {}
for line in path.read_text().splitlines():
obj = json.loads(line)
trial_id = obj.get("trial_id")
if trial_id is None:
continue
trial = trials.setdefault(trial_id, {"attrs": {}, "state": None})
if obj.get("op_code") == 8 and "user_attr" in obj:
trial["attrs"].update(obj["user_attr"])
elif obj.get("op_code") == 6:
trial["state"] = obj.get("state")
completed = [
trial["attrs"]
for trial in trials.values()
if trial["state"] == 1 and "refusals" in trial["attrs"]
]
if not completed:
raise ValueError(f"No completed trials found in {path}")
completed.sort(
key=lambda attrs: (
attrs.get("refusals", 10**9),
attrs.get("overrefusals", 10**9),
attrs.get("kl_divergence", 10**9),
)
)
return completed[0]
def load_heretic_best(path: Path) -> dict[str, Any]:
if path.name == "batch_summary.json":
summary = json.loads(path.read_text())
trials = summary.get("pareto_trials", [])
if not trials:
raise ValueError(f"No pareto trials found in {path}")
return trials[0]
return load_best_from_study(path)
def format_float(value: Any, digits: int = 4) -> str:
if value is None:
return "n/a"
return f"{float(value):.{digits}f}"
def main() -> None:
args = parse_args()
rows = []
for spec in args.spec:
label, icon_path_str, her_path_str = spec.split("|", 2)
icon_path = Path(icon_path_str)
her_path = Path(her_path_str)
icon_best = load_iconoclast_best(icon_path)
her_best = load_heretic_best(her_path)
rows.append(
{
"label": label,
"iconoclast": {
"refusals": icon_best.get("refusals"),
"overrefusals": icon_best.get("overrefusals", 0),
"kl_divergence": icon_best.get("kl_divergence"),
"harmful_marker_hits": icon_best.get("harmful_marker_hits"),
"harmful_compliance_score": icon_best.get(
"harmful_compliance_score"
),
"trial_index": icon_best.get("index"),
},
"heretic": {
"refusals": her_best.get("refusals"),
"overrefusals": her_best.get("overrefusals", 0),
"kl_divergence": her_best.get("kl_divergence"),
"trial_index": her_best.get("index"),
},
}
)
if args.format == "json":
print(json.dumps(rows, indent=2))
return
print(
"| Model | Iconoclast Refusals | Iconoclast Overrefusals | Iconoclast KL | Heretic Refusals | Heretic Overrefusals | Heretic KL | Verdict |"
)
print("| --- | --- | --- | --- | --- | --- | --- | --- |")
for row in rows:
icon = row["iconoclast"]
her = row["heretic"]
verdict = (
"Iconoclast"
if (
(icon["refusals"], icon["overrefusals"], icon["kl_divergence"])
< (her["refusals"], her["overrefusals"], her["kl_divergence"])
)
else "Heretic"
)
print(
"| "
+ " | ".join(
[
row["label"],
str(icon["refusals"]),
str(icon["overrefusals"]),
format_float(icon["kl_divergence"]),
str(her["refusals"]),
str(her["overrefusals"]),
format_float(her["kl_divergence"]),
verdict,
]
)
+ " |"
)
if __name__ == "__main__":
main()
|