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"""
This script is used to convert https://github.com/Open-Reasoner-Zero/Open-Reasoner-Zero
Usage:
python scripts/data/rlvr/open_reasoner.py --push_to_hub
python scripts/data/rlvr/open_reasoner.py --push_to_hub --hf_entity ai2-adapt-dev
"""
from collections import defaultdict
from dataclasses import dataclass
import os
from typing import Optional
import datasets
from huggingface_hub import HfApi
from huggingface_hub.repocard import RepoCard
from transformers import HfArgumentParser
@dataclass
class Args:
push_to_hub: bool = False
file_path: str = "orz_math_57k_collected.json"
hf_entity: Optional[str] = None
def main(args: Args):
# download https://github.com/Open-Reasoner-Zero/Open-Reasoner-Zero/raw/refs/heads/main/data/orz_math_57k_collected.json
import requests
import json
if not os.path.exists(args.file_path):
url = "https://github.com/Open-Reasoner-Zero/Open-Reasoner-Zero/raw/refs/heads/main/data/orz_math_57k_collected.json"
response = requests.get(url)
with open(args.file_path, "w") as f:
f.write(response.text)
with open(args.file_path, "r") as f:
data = json.load(f)
table = defaultdict(list)
for item in data:
assert len(item) == 2 # 1 question 2 ground truth
table["messages"].append([
{"role": "user", "content": item[0]["value"]},
{"role": "assistant", "content": item[1]["ground_truth"]["value"]},
])
table["ground_truth"].append(item[1]["ground_truth"]["value"])
table["dataset"].append("math")
dataset = datasets.Dataset.from_dict(table)
if args.push_to_hub:
api = HfApi()
if not args.hf_entity:
args.hf_entity = HfApi().whoami()["name"]
file_path = args.file_path.split(".json")[0]
repo_id = f"{args.hf_entity}/rlvr_{file_path}"
print(f"Pushing dataset to Hub: {repo_id}")
dataset.push_to_hub(repo_id)
api.upload_file(
path_or_fileobj=__file__,
path_in_repo="create_dataset.py",
repo_type="dataset",
repo_id=repo_id,
)
# Add RepoCard
repo_card = RepoCard(
content=f"""\
# Open Reasoner Dataset
This dataset is converted from [Open-Reasoner-Zero](https://github.com/Open-Reasoner-Zero/Open-Reasoner-Zero)'s math dataset.
Check out https://github.com/allenai/open-instruct/blob/main/scripts/data/rlvr/open_reasoner.py for the conversion script.
## Dataset Format
The dataset contains math problems and their solutions in a conversational format:
- `messages`: List of message dictionaries with user questions and assistant answers
- `ground_truth`: The correct solution for each problem
- `dataset`: Always "math" to indicate this is from the math datases""")
repo_card.push_to_hub(
repo_id,
repo_type="dataset",
)
if __name__ == "__main__":
parser = HfArgumentParser((Args))
main(*parser.parse_args_into_dataclasses())
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