Files
DataPipeline/scripts/cache_h5.py
T
2026-03-30 20:58:51 +08:00

78 lines
2.7 KiB
Python

"""JSONL to H5 caching script.
Tokenize JSONL files and pack them into HDF5 format.
Usage:
python scripts/cache_h5.py pt ./dataset/chinese-c4-pretrain
python scripts/cache_h5.py sft ./dataset/belle-sft --pack-size 4096 --strategy alpaca
python scripts/cache_h5.py sft ./dataset/Ling-Coder-sft --tokenizer ./my_tokenizer.json
"""
import argparse
import os
from pipeline import BpeTokenizer, ProcessorFactory, cache_jsonl
from pipeline.io import IOHandler
def main():
parser = argparse.ArgumentParser(description="JSONL -> H5 cache")
parser.add_argument("type", choices=["pt", "sft", "dpo"], help="Processor type")
parser.add_argument("input_dir", help="Directory containing JSONL files")
parser.add_argument("-o", "--output-dir", default=None,
help="H5 output dir (default: <input_dir>/cached)")
parser.add_argument("-t", "--tokenizer", default="./tokenizer.json",
help="Tokenizer path (default: ./tokenizer.json)")
parser.add_argument("-s", "--strategy", default=None,
help="Prompt strategy: chatml, alpaca (default: chatml)")
parser.add_argument("-p", "--pack-size", type=int, default=-1,
help="Pack size, <=0 to disable (default: -1)")
parser.add_argument("--pad-value", type=int, default=1,
help="Padding value (default: 1)")
args = parser.parse_args()
jsonl_files = IOHandler.fetch_files(args.input_dir, suffix=".jsonl")
if not jsonl_files:
print(f"[ERROR] No JSONL files found in {args.input_dir}")
return
print(f"Found {len(jsonl_files)} JSONL files:")
for f in jsonl_files:
print(f" - {f}")
if not os.path.exists(args.tokenizer):
print(f"[ERROR] Tokenizer not found: {args.tokenizer}")
return
tokenizer = BpeTokenizer(args.tokenizer)
print(f"Tokenizer loaded: vocab_size={len(tokenizer)}")
if args.strategy:
processor = ProcessorFactory.create_with_strategy_name(
args.type, tokenizer, args.strategy
)
else:
processor = ProcessorFactory.create(args.type, tokenizer)
print(f"Processor: {args.type} ({processor.__class__.__name__})")
print(f"Output keys: {processor.output_keys}")
output_dir = args.output_dir or os.path.join(args.input_dir, "cached")
print(f"\nStart caching...")
if args.pack_size > 0:
print(f" pack_size={args.pack_size}, pad_value={args.pad_value}")
else:
print(f" no packing")
cache_jsonl(
files=jsonl_files,
output_dir=output_dir,
processor=processor,
pack_size=args.pack_size,
pad_value=args.pad_value,
)
print(f"\nDone! Output saved to {output_dir}")
if __name__ == "__main__":
main()