File size: 2,995 Bytes
73aeb35 | 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 | """Download RLCSD training/eval parquet files from a HuggingFace dataset repo.
The verl launcher (`scripts/_run_verl.sh`) expects each dataset to live at
`data/verl/<DATASET_NAME>/{train,val}.parquet`. This script mirrors the upstream
HF repo layout into that directory.
Example:
# download every dataset referenced by the shipped configs
python scripts/download_data.py --all
# only the kk_4to8 train split
python scripts/download_data.py --dataset kk_4to8 --split train
"""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
DEFAULT_REPO = "Leyiii/RLCSD"
DEFAULT_LOCAL_ROOT = Path("data/verl")
# (dataset_name, split). dataset_name matches `train_dataset` / `val_dataset` in configs.
DATASETS = [
("deepmath_filtered_level5_7", "train"), # Qwen3-1.7B math
("deepmath_filtered_level6_8", "train"), # Qwen3-4B math
("deepmath_filtered_level7_10", "train"), # Qwen3-8B + Olmo math
("amc23+aime24+aime25", "val"), # math eval
("kk_4to8", "train"), # logic train
("kk_4to8_test+kk_9+kk_10+kk_11", "val"), # logic eval
]
def download(repo_id: str, dataset_name: str, split: str, dst_root: Path) -> Path:
from huggingface_hub import hf_hub_download
remote_path = f"{dataset_name}/{split}.parquet"
local_dir = dst_root / dataset_name
local_dir.mkdir(parents=True, exist_ok=True)
local_path = hf_hub_download(
repo_id=repo_id,
filename=remote_path,
repo_type="dataset",
local_dir=str(dst_root),
)
return Path(local_path)
def main() -> int:
p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
p.add_argument("--repo", default=DEFAULT_REPO, help="HF dataset repo to pull from")
p.add_argument("--dst", default=str(DEFAULT_LOCAL_ROOT), help="Local data root (default data/verl)")
g = p.add_mutually_exclusive_group()
g.add_argument("--all", action="store_true", help="Download every dataset")
g.add_argument("--dataset", help="Single dataset name (e.g. kk_4to8)")
p.add_argument("--split", choices=("train", "val"), help="Split to download (with --dataset)")
args = p.parse_args()
dst_root = Path(args.dst)
dst_root.mkdir(parents=True, exist_ok=True)
if args.all or (not args.dataset):
targets = DATASETS
else:
if args.split is None:
print("--split is required when --dataset is given", file=sys.stderr)
return 2
targets = [(args.dataset, args.split)]
for name, split in targets:
try:
path = download(args.repo, name, split, dst_root)
print(f"OK {name}/{split}.parquet -> {path}")
except Exception as exc:
print(f"FAIL {name}/{split}.parquet: {exc}", file=sys.stderr)
return 1
return 0
if __name__ == "__main__":
sys.exit(main())
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