dataset_0.py

# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.

"""MiniF2F+Informal in Isabelle
Loading script author: Sean Welleck
"""

import re
import glob
import json
import os
import datasets
from pathlib import Path


_CITATION = """\
@inproceedings{jiang2023draft,
    title={Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs},
    author={Albert Qiaochu Jiang and Sean Welleck and Jin Peng Zhou and Timothee Lacroix and Jiacheng Liu and Wenda Li and Mateja Jamnik and Guillaume Lample and Yuhuai Wu},
    booktitle={The Eleventh International Conference on Learning Representations },
    year={2023},
    url={https://openreview.net/forum?id=SMa9EAovKMC}
}
@inproceedings{zheng2022miniff,
    title={miniF2F: a cross-system benchmark for formal Olympiad-level mathematics},
    author={Kunhao Zheng and Jesse Michael Han and Stanislas Polu},
    booktitle={International Conference on Learning Representations},
    year={2022},
    url={https://openreview.net/forum?id=9ZPegFuFTFv}
}
"""

_DESCRIPTION = """\
MiniF2F is a formal mathematics benchmark (translated across multiple formal systems) consisting of exercise statements from olympiads (AMC, AIME, IMO) as well as high-school and undergraduate maths classes.
This dataset contains formal statements in Isabelle. Each statement is paired with an informal statement and 
an informal proof, as described in Draft, Sketch, Prove [Jiang et al 2023].
The problems in this dataset use the most recent facebookresearch/miniF2F commit on July 3, 2023. 
"""

#_HOMEPAGE = "https://github.com/facebookresearch/miniF2F" 
_HOMEPAGE = "https://github.com/xyc-cs/miniF2F"
_LICENSE = "MIT"

#_MINIF2F_COMMIT = 'bfb337d6848c81baab18bb3d4e9f80625ed63d5d'  # single_json: 0826c5173d8b2ef67c616a8170240034094837d6
_MINIF2F_COMMIT = '0826c5173d8b2ef67c616a8170240034094837d6'

_URLS = {
    "minif2f_repo": "https://github.com/xyc-cs/miniF2F/archive/%s.zip" % _MINIF2F_COMMIT #https://github.com/xyc-cs/miniF2F/archive/5271ddec788677c815cf818a06f368ef6498a106.zip
}

_ISABELLEDIR = 'miniF2F-%s/isabelle' % _MINIF2F_COMMIT
_INFORMALDIR = 'miniF2F-%s/informal' % _MINIF2F_COMMIT

_NAMES = [
    'miniF2F-isabelle-informal',
]

VERSION = "1.1.0"


class MiniF2F(datasets.GeneratorBasedBuilder):
    """MiniF2F+Informal in Isabelle"""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name=name, version=VERSION, description=name) for name in _NAMES
    ]

    DEFAULT_CONFIG_NAME = "miniF2F-isabelle-informal"

    def _info(self):
        features = datasets.Features(
            {
                "problem_name": datasets.Value("string"),
                "formal_statement": datasets.Value("string"),
                "informal_statement": datasets.Value("string"),
                "informal_discuss": datasets.Value("string"),
                "header": datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        urls = _URLS
        data_dir = dl_manager.download_and_extract(urls)

        minif2f_repo_dir = data_dir['minif2f_repo']

        def extract_theorem(text):
            # extract = re.findall(r"(theorem.*?:.*?(?=by |using |proof|sorry))[\s]*", text, re.DOTALL)[0].strip()
            # assert extract != ''
            extract = ''
            return extract

        def extract_header(text):
            # extract = re.findall(r"(.*?)theorem.*?", text, re.DOTALL)[0]
            # assert extract != ''
            extract = ''
            return extract

        splits = {'valid': [], 'test': []}
        for split in ['valid', 'test']:
            for f in glob.glob(
                    os.path.join(minif2f_repo_dir, _ISABELLEDIR, '%s/*.json' % split)
            ):
                text = open(f).read()
                name = Path(f).name.replace('.json', '')
                thm = extract_theorem(text)
                header = extract_header(text)
                informal = json.load(open(
                    os.path.join(minif2f_repo_dir, _INFORMALDIR, '%s/%s.json' % (split, name))
                ))

                splits[split].append({
                    'problem_name': name,
                    'formal_statement': thm,
                    'informal_statement': informal['informal_statement'],
                    'informal_discuss': informal['informal_discuss']
                    #'header': header
                })

        #assert len(splits['valid']) == 5
        #assert len(splits['test']) == 5

        return [
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "split": "valid",
                    "examples": splits['valid']
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "split": "test",
                    "examples": splits['test']
                },
            ),
        ]

    def _generate_examples(self, split, examples):
        for example in examples:
            key = example["problem_name"]
            yield key, example