| |
| """Evaluate an already-quantized model directory against a BF16 reference. |
| |
| `run_lane.py` always converts from BF16 first, so it cannot measure a model |
| that arrives ready-made (an official release, a QAD output, a downloaded |
| checkpoint). This is the missing half: point it at two directories and it |
| produces the same ΔBPC JSON that the lanes report. |
| |
| Both directories must be lalamo-loadable after `make_lalamo_eval_copy.py`; the |
| script builds the eval copies itself. |
| |
| Usage: |
| python scripts/eval_external_model.py \ |
| --bf16-dir /kaggle/working/bf16-lalamo \ |
| --candidate-dir /kaggle/working/official \ |
| --corpus data/eval_en_wikitext2_dedup.txt --corpus data/eval_ja_wikipedia_dedup.txt \ |
| --out /kaggle/working/official-eval |
| """ |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import subprocess |
| import sys |
| from pathlib import Path |
|
|
| HERE = Path(__file__).resolve().parent |
| LANGS = {"wikitext2": "en", "wikipedia": "ja"} |
|
|
|
|
| def language_of(corpus: Path) -> str: |
| name = corpus.name.lower() |
| for marker, lang in LANGS.items(): |
| if marker in name: |
| return lang |
| return name.split("_")[1] if name.startswith("eval_") and "_" in name else "unknown" |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--bf16-dir", type=Path, required=True, help="reference BF16 model directory") |
| parser.add_argument("--candidate-dir", type=Path, required=True, help="model to measure") |
| parser.add_argument("--corpus", type=Path, action="append", required=True) |
| parser.add_argument("--out", type=Path, required=True) |
| parser.add_argument("--max-sequences", type=int, default=100) |
| parser.add_argument("--max-tokens", type=int, default=128) |
| parser.add_argument("--min-tokens", type=int, default=16) |
| parser.add_argument("--dtype", default="float32") |
| parser.add_argument("--dry-run", action="store_true") |
| args = parser.parse_args() |
|
|
| args.out.mkdir(parents=True, exist_ok=True) |
| copies = {} |
| for label, source in (("bf16", args.bf16_dir), ("candidate", args.candidate_dir)): |
| destination = args.out / f"{label}-eval" |
| copies[label] = destination |
| command = [ |
| sys.executable, |
| str(HERE / "make_lalamo_eval_copy.py"), |
| "--source", |
| str(source), |
| "--dest", |
| str(destination), |
| ] |
| if args.dry_run: |
| print("dry-run:", " ".join(command)) |
| else: |
| subprocess.run(command, check=True) |
|
|
| results = {} |
| for corpus in args.corpus: |
| lang = language_of(corpus) |
| payload_path = args.out / f"{lang}.json" |
| command = [ |
| sys.executable, |
| str(HERE / "eval_quantized.py"), |
| "--bf16-dir", |
| str(copies["bf16"]), |
| "--candidate-dir", |
| str(copies["candidate"]), |
| "--corpus", |
| str(corpus), |
| "--max-sequences", |
| str(args.max_sequences), |
| "--max-tokens", |
| str(args.max_tokens), |
| "--min-tokens", |
| str(args.min_tokens), |
| "--dtype", |
| args.dtype, |
| "--json-out", |
| str(payload_path), |
| ] |
| if args.dry_run: |
| print("dry-run:", " ".join(command)) |
| continue |
| subprocess.run(command, check=True) |
| payload = json.loads(payload_path.read_text()) |
| delta = (payload["bpc_candidate"] / payload["bpc_bf16"] - 1) * 100 |
| results[lang] = { |
| "ppl": payload["candidate_ppl"], |
| "bf16_ppl": payload["bf16_ppl"], |
| "bpc_delta_pct": round(delta, 2), |
| } |
| print(f"{lang}: {payload['candidate_ppl']:.3f} bpc_delta={delta:+.2f}%", flush=True) |
|
|
| if args.dry_run: |
| return |
| (args.out / "summary.json").write_text( |
| json.dumps(results, indent=2, ensure_ascii=False) + "\n", encoding="utf-8" |
| ) |
| print("=== FINAL ===", flush=True) |
| print(json.dumps(results, indent=1), flush=True) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
