# Copyright 2024 Bytedance Ltd. 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 GSM8k dataset to parquet format """ import argparse import os import re import datasets from verl.utils.hdfs_io import copy, makedirs def extract_solution(solution_str): solution = re.search("#### (\\-?[0-9\\.\\,]+)", solution_str) assert solution is not None final_solution = solution.group(0) final_solution = final_solution.split("#### ")[1].replace(",", "") return final_solution if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--local_dir", default="~/data/gsm8k") parser.add_argument("--hdfs_dir", default=None) args = parser.parse_args() data_source = "openai/gsm8k" dataset = datasets.load_dataset(data_source, "main") train_dataset = dataset["train"] test_dataset = dataset["test"] instruction_following = 'Let\'s think step by step and output the final answer after "####".' # add a row to each data item that represents a unique id def make_map_fn(split): def process_fn(example, idx): question_raw = example.pop("question") question = question_raw + " " + instruction_following answer_raw = example.pop("answer") solution = extract_solution(answer_raw) data = { "data_source": data_source, "prompt": [ { "role": "user", "content": question, } ], "ability": "math", "reward_model": {"style": "rule", "ground_truth": solution}, "extra_info": { "split": split, "index": idx, "answer": answer_raw, "question": question_raw, }, } return data return process_fn train_dataset = train_dataset.map(function=make_map_fn("train"), with_indices=True) test_dataset = test_dataset.map(function=make_map_fn("test"), with_indices=True) local_dir = args.local_dir hdfs_dir = args.hdfs_dir train_dataset.to_parquet(os.path.join(local_dir, "train.parquet")) test_dataset.to_parquet(os.path.join(local_dir, "test.parquet")) if hdfs_dir is not None: makedirs(hdfs_dir) copy(src=local_dir, dst=hdfs_dir)