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f1a4107 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 | #!/usr/bin/env python3
"""Fail fast when an experiment mixes incompatible eval/calibration settings."""
from __future__ import annotations
import argparse
import hashlib
import json
from collections import defaultdict
from pathlib import Path
def sha256_file(path: Path) -> str:
digest = hashlib.sha256()
with open(path, "rb") as file:
for chunk in iter(lambda: file.read(1 << 20), b""):
digest.update(chunk)
return digest.hexdigest()[:16]
def expected_eval(config: dict, corpus: str) -> dict:
eval_cfg = config["eval"]
corpus_path = Path(corpus)
return {
"corpus": str(corpus_path),
"corpus_sha256": sha256_file(corpus_path),
"max_sequences": eval_cfg["max_sequences"],
"max_tokens": eval_cfg["max_tokens"],
"min_tokens": eval_cfg["min_tokens"],
}
def config_hash(value: dict) -> str:
return hashlib.sha256(json.dumps(value, sort_keys=True).encode("utf-8")).hexdigest()[:16]
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--config", type=Path, required=True)
parser.add_argument("--root", type=Path, default=None)
parser.add_argument("--json-out", type=Path, default=None)
args = parser.parse_args()
config = json.loads(args.config.read_text())
root = args.root or args.config.parent
eval_cfg = config["eval"]
calib_cfg = config["calibration"]
corpora = {Path(path).name: path for path in eval_cfg["corpora"].values()}
expected_by_name = {name: expected_eval(config, path) for name, path in corpora.items()}
errors: list[str] = []
warnings: list[str] = []
ppl_rows = []
baseline_by_corpus: dict[str, list[float]] = defaultdict(list)
for path in sorted(root.rglob("ppl_*.json")):
data = json.loads(path.read_text())
corpus_name = Path(data.get("corpus", "")).name
row = {"path": str(path), "corpus": corpus_name}
ppl_rows.append(row)
if corpus_name not in corpora:
errors.append(f"{path}: unknown corpus {corpus_name!r}")
continue
expected = expected_by_name[corpus_name]
if data.get("chunks") != expected["max_sequences"]:
errors.append(
f"{path}: chunks={data.get('chunks')} != config max_sequences={expected['max_sequences']}"
)
if data.get("tokens") is not None and data.get("chunks"):
approx = data["chunks"] * expected["max_tokens"] - data["chunks"]
if abs(int(data["tokens"]) - approx) > expected["max_sequences"]:
warnings.append(
f"{path}: tokens={data.get('tokens')} differs from approx {approx}"
)
if data.get("config"):
if data["config"] != expected:
errors.append(f"{path}: embedded eval config differs from model config")
if data.get("config_hash") != config_hash(expected):
errors.append(f"{path}: config_hash mismatch")
else:
warnings.append(f"{path}: legacy result without config/config_hash")
if "bf16_ppl" in data:
baseline_by_corpus[corpus_name].append(float(data["bf16_ppl"]))
for corpus_name, values in baseline_by_corpus.items():
if max(values) - min(values) > 0.01:
errors.append(
f"BF16 baseline drift for {corpus_name}: {sorted(set(round(value, 4) for value in values))}"
)
calibration_rows = []
calibration_corpora: set[Path] = set(
Path(path) for path in calib_cfg.get("corpora", {}).values()
)
qad_corpus = config.get("qad", {}).get("corpus")
if qad_corpus:
calibration_corpora.add(Path(qad_corpus))
for path in sorted(root.rglob("calibration.json")):
data = json.loads(path.read_text())
row = {"path": str(path), "corpus": Path(data.get("corpus", "")).name}
calibration_rows.append(row)
if data.get("corpus"):
calibration_corpora.add(Path(data["corpus"]))
checks = {
"samples": calib_cfg["samples"],
"max_tokens": calib_cfg["max_tokens"],
"output_block": calib_cfg["output_block"],
}
for key, expected in checks.items():
if data.get(key) != expected:
errors.append(f"{path}: {key}={data.get(key)!r} != config {expected!r}")
damping = float(data.get("damping", -1))
if abs(damping - float(calib_cfg["damping"])) > 1e-12:
errors.append(f"{path}: damping={damping} != config {calib_cfg['damping']}")
eval_corpora = {Path(path) for path in corpora.values()}
def long_lines(path: Path) -> set[str]:
return {
line.strip()
for line in path.read_text(encoding="utf-8").splitlines()
if len(line.strip()) >= 20
}
for eval_corpus in sorted(eval_corpora):
if not eval_corpus.exists():
continue
lines = [
line.strip()
for line in eval_corpus.read_text(encoding="utf-8").splitlines()
if len(line.strip()) >= 20
]
duplicates = len(lines) - len(set(lines))
if duplicates:
errors.append(f"{eval_corpus}: {duplicates} duplicate long lines; dedup required")
overlap_checks = 0
for calibration_corpus in sorted(calibration_corpora):
if not calibration_corpus.exists():
errors.append(f"missing calibration corpus: {calibration_corpus}")
continue
for eval_corpus in sorted(eval_corpora):
if not eval_corpus.exists():
errors.append(f"missing eval corpus: {eval_corpus}")
continue
overlap_checks += 1
if calibration_corpus.resolve() == eval_corpus.resolve():
errors.append(f"calibration and eval use the same file: {eval_corpus}")
continue
overlap = long_lines(calibration_corpus) & long_lines(eval_corpus)
if overlap:
sample = next(iter(overlap))[:80]
errors.append(
f"corpus overlap: {calibration_corpus} vs {eval_corpus} "
f"({len(overlap)} lines, e.g. {sample!r})"
)
report = {
"config": str(args.config),
"config_name": config.get("name"),
"ppl_rows": len(ppl_rows),
"calibration_rows": len(calibration_rows),
"corpus_overlap_checks": overlap_checks,
"errors": errors,
"warnings": warnings,
"ok": not errors,
}
text = json.dumps(report, indent=2, ensure_ascii=False)
print(text)
if args.json_out:
args.json_out.parent.mkdir(parents=True, exist_ok=True)
args.json_out.write_text(text + "\n")
raise SystemExit(0 if not errors else 1)
if __name__ == "__main__":
main()
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