from __future__ import annotations import argparse import json from pathlib import Path import numpy as np from transformers import AutoTokenizer from kawk50m.cli import configure_utf8_stdio from scripts.tokenize_corpus import tokenize_split def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser( description="Tokenize one clean JSONL shard into a uint16 token part." ) parser.add_argument("--input", required=True) parser.add_argument("--tokenizer-dir", required=True) parser.add_argument("--output", required=True) parser.add_argument("--batch-size", type=int, default=64) return parser.parse_args() def main() -> None: configure_utf8_stdio() args = parse_args() input_path = Path(args.input) output_path = Path(args.output) metadata_path = output_path.with_suffix(".json") if not input_path.is_file(): raise FileNotFoundError(input_path) if output_path.exists() or metadata_path.exists(): raise FileExistsError(f"Refusing to overwrite token part: {output_path}") if args.batch_size <= 0: raise ValueError("--batch-size must be positive") output_path.parent.mkdir(parents=True, exist_ok=True) tokenizer = AutoTokenizer.from_pretrained( args.tokenizer_dir, use_fast=False, legacy=True ) tokenizer.model_max_length = int(1e30) if len(tokenizer) > np.iinfo(np.uint16).max: raise ValueError("uint16 output requires a vocabulary no larger than 65,535") if tokenizer.eos_token_id is None: raise ValueError("Tokenizer must define eos_token_id") summary = tokenize_split( split=input_path.stem, paths=[input_path], tokenizer=tokenizer, output_path=output_path, batch_size=args.batch_size, max_tokens=None, ) summary["input"] = str(input_path) with metadata_path.open("w", encoding="utf-8") as handle: json.dump(summary, handle, ensure_ascii=False, indent=2) handle.write("\n") print(json.dumps(summary, ensure_ascii=False)) if __name__ == "__main__": main()