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# 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_aime2024")
parser.add_argument("--hdfs_dir", default=None)
args = parser.parse_args()
data_path = "BytedTsinghua-SIA/AIME-2024"
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)
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