# Copyright 2024 Bytedance Ltd. and/or its affiliates # Copyright 2023-2024 SGLang Team # Copyright 2025 ModelBest Inc. and/or its affiliates # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Preprocess the DAPO-Math-17k dataset to multiturn format """ import argparse import os import datasets from verl.utils.hdfs_io import copy, makedirs if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--local_dir", default="~/data/retool_dapo") parser.add_argument("--hdfs_dir", default=None) args = parser.parse_args() data_path = "BytedTsinghua-SIA/DAPO-Math-17k" dataset = datasets.load_dataset(data_path, "default") train_dataset = dataset["train"] # add a row to each data item that represents a unique id def make_map_fn(split): def process_fn(example, idx): orig_extra_info = example.pop("extra_info") extra_info = orig_extra_info.copy() extra_info["need_tools_kwargs"] = True extra_info["tools_kwargs"] = { "code_interpreter": { "create_kwargs": { "ground_truth": example["reward_model"]["ground_truth"], }, }, } example["extra_info"] = extra_info return example return process_fn train_dataset = train_dataset.map(function=make_map_fn("train"), with_indices=True) local_dir = args.local_dir hdfs_dir = args.hdfs_dir train_dataset.to_parquet(os.path.join(local_dir, "train.parquet")) if hdfs_dir is not None: makedirs(hdfs_dir) copy(src=local_dir, dst=hdfs_dir)