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"""Apply the precommitted sampling-temperature and review selection rules."""
from __future__ import annotations
import argparse
import json
import time
import tomllib
from pathlib import Path
from compare_evals import exact_two_sided_sign_p, read_traces, solved, task_key
def outcomes(path: Path) -> dict[str, bool]:
run_dir = path if path.is_dir() else path.parent
config = tomllib.loads((run_dir / "config.toml").read_text())
if config.get("num_tasks") != 32 or config.get("num_rollouts", 1) != 1:
raise ValueError(f"selection run is not the precommitted 32x1 protocol: {path}")
traces = read_traces(path)
result = {task_key(trace): solved(trace) for trace in traces}
if len(result) != len(traces):
raise ValueError(f"selection run contains duplicate task keys: {path}")
if len(result) != 32:
raise ValueError(
f"selection run is incomplete: expected 32 distinct traces, "
f"observed {len(result)}: {path}"
)
return result
def compare(path_a: Path, path_b: Path, label_a: str, label_b: str) -> dict:
a = outcomes(path_a)
b = outcomes(path_b)
if a.keys() != b.keys():
raise ValueError(
f"paired selection runs contain different task keys: {path_a} vs {path_b}"
)
keys = a.keys() | b.keys()
a_only = sum(a.get(key, False) and not b.get(key, False) for key in keys)
b_only = sum(b.get(key, False) and not a.get(key, False) for key in keys)
return {
f"{label_a}_successes": sum(a.values()),
f"{label_b}_successes": sum(b.values()),
f"{label_a}_only": a_only,
f"{label_b}_only": b_only,
"observed_task_union": len(keys),
f"missing_from_{label_a}": len(b.keys() - a.keys()),
f"missing_from_{label_b}": len(a.keys() - b.keys()),
}
def challenger_gate(
tb2: dict, swe: dict, default_label: str, challenger_label: str
) -> dict:
default_only = sum(
result[f"{default_label}_only"] for result in (tb2, swe)
)
challenger_only = sum(
result[f"{challenger_label}_only"] for result in (tb2, swe)
)
sign_p = exact_two_sided_sign_p(default_only, challenger_only)
no_suite_regression = all(
result[f"{challenger_label}_successes"]
>= result[f"{default_label}_successes"]
for result in (tb2, swe)
)
positive_paired_advantage = challenger_only > default_only
significant = sign_p is not None and sign_p <= 0.10
return {
"challenger_qualifies": (
no_suite_regression and positive_paired_advantage and significant
),
"rule": {
"no_suite_regression": no_suite_regression,
"positive_combined_paired_advantage": positive_paired_advantage,
"combined_exact_two_sided_sign_test_p_le_0_10": significant,
},
"combined": {
f"{default_label}_only": default_only,
f"{challenger_label}_only": challenger_only,
"discordant_tasks": default_only + challenger_only,
"exact_two_sided_sign_test_p": sign_p,
},
"terminal_bench_2": tb2,
"swe_bench_verified": swe,
}
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("no_review_t02_tb2", type=Path)
parser.add_argument("review_t02_tb2", type=Path)
parser.add_argument("no_review_t06_tb2", type=Path)
parser.add_argument("review_t06_tb2", type=Path)
parser.add_argument("no_review_t02_swe", type=Path)
parser.add_argument("review_t02_swe", type=Path)
parser.add_argument("no_review_t06_swe", type=Path)
parser.add_argument("review_t06_swe", type=Path)
parser.add_argument("stock_t02_tb2", type=Path)
parser.add_argument("stock_t06_tb2", type=Path)
parser.add_argument("stock_t02_swe", type=Path)
parser.add_argument("stock_t06_swe", type=Path)
args = parser.parse_args()
# The fixed development wave can finish while the shared sandbox pool is
# saturated. An independent watcher resumes only terminal infrastructure
# failures on the same task indices. Do not let those transient failures
# influence harness selection while that repair is still in progress.
paths = [Path(value) for value in vars(args).values()]
if any("step150-" in str(path) for path in paths):
marker = Path(__file__).resolve().parent.parent / "state" / "step150-infra-repair-complete"
deadline = time.monotonic() + 8 * 60 * 60
while not marker.exists():
if time.monotonic() >= deadline:
raise TimeoutError(f"timed out waiting for infrastructure repair: {marker}")
time.sleep(10)
temperature_gate = challenger_gate(
compare(
args.no_review_t06_tb2,
args.no_review_t02_tb2,
"official_t06",
"low_t02",
),
compare(
args.no_review_t06_swe,
args.no_review_t02_swe,
"official_t06",
"low_t02",
),
"official_t06",
"low_t02",
)
temperature = "0.2" if temperature_gate["challenger_qualifies"] else "0.6"
review_gates = {
"0.2": challenger_gate(
compare(
args.no_review_t02_tb2,
args.review_t02_tb2,
"no_review",
"review",
),
compare(
args.no_review_t02_swe,
args.review_t02_swe,
"no_review",
"review",
),
"no_review",
"review",
),
"0.6": challenger_gate(
compare(
args.no_review_t06_tb2,
args.review_t06_tb2,
"no_review",
"review",
),
compare(
args.no_review_t06_swe,
args.review_t06_swe,
"no_review",
"review",
),
"no_review",
"review",
),
}
custom_choice = (
"review" if review_gates[temperature]["challenger_qualifies"] else "noreview"
)
custom_paths = {
("0.2", "noreview", "tb2"): args.no_review_t02_tb2,
("0.2", "review", "tb2"): args.review_t02_tb2,
("0.6", "noreview", "tb2"): args.no_review_t06_tb2,
("0.6", "review", "tb2"): args.review_t06_tb2,
("0.2", "noreview", "swe"): args.no_review_t02_swe,
("0.2", "review", "swe"): args.review_t02_swe,
("0.6", "noreview", "swe"): args.no_review_t06_swe,
("0.6", "review", "swe"): args.review_t06_swe,
}
stock_paths = {
("0.2", "tb2"): args.stock_t02_tb2,
("0.6", "tb2"): args.stock_t06_tb2,
("0.2", "swe"): args.stock_t02_swe,
("0.6", "swe"): args.stock_t06_swe,
}
# The aligned scaffold is the evidence-backed default because the SFT
# corpus used its exact prompt/schema. Stock may replace it only on strong,
# paired evidence of non-inferiority on each suite and a combined advantage.
scaffold_gate = challenger_gate(
compare(
custom_paths[(temperature, custom_choice, "tb2")],
stock_paths[(temperature, "tb2")],
"selected_custom",
"stock",
),
compare(
custom_paths[(temperature, custom_choice, "swe")],
stock_paths[(temperature, "swe")],
"selected_custom",
"stock",
),
"selected_custom",
"stock",
)
choice = "stock" if scaffold_gate["challenger_qualifies"] else custom_choice
print(
json.dumps(
{
"temperature": temperature,
"choice": choice,
"temperature_decision": temperature_gate,
"review_decisions": review_gates,
"scaffold_decision": scaffold_gate,
},
indent=2,
)
)
if __name__ == "__main__":
main()
|