aio-passages.py

# Copyright 2020 The HuggingFace Datasets Authors.
# Copyright 2023 Masatoshi Suzuki (@singletongue).
#
# 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.
import io
from typing import Iterator, List, Tuple

import datasets
import pyarrow as pa


_DESCRIPTION = (
    "書籍『大規模言語モデル入門』で使用する、「AI王」コンペティションのパッセージデータセットです。"
    "GitHub リポジトリ cl-tohoku/quiz-datasets で公開されているデータセットを利用しています。"
)
_HOMEPAGE = "https://github.com/cl-tohoku/quiz-datasets"
_LICENSE = (
    "本データセットで使用している Wikipedia のコンテンツは、クリエイティブ・コモンズ表示・継承ライセンス 3.0 (CC BY-SA 3.0) "
    "および GNU 自由文書ライセンス (GFDL) の下に配布されているものです。"
)

_URL_BASE = "https://github.com/cl-tohoku/quiz-datasets/releases/download"
_URL = f"{_URL_BASE}/v1.0.1/passages.jawiki-20220404-c400-large.jsonl.gz"


class AioPassages(datasets.ArrowBasedBuilder):
    VERSION = datasets.Version("1.0.0")

    def _info(self) -> datasets.DatasetInfo:
        features = datasets.Features({
            "id": datasets.Value("int32"),
            "pageid": datasets.Value("int32"),
            "revid": datasets.Value("int32"),
            "text": datasets.Value("string"),
            "section": datasets.Value("string"),
            "title": datasets.Value("string"),
        })
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            features=features,
        )

    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
        filepath = dl_manager.download_and_extract(_URL)

        split_generators = [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": filepath})]
        return split_generators

    def _generate_tables(self, filepath: str, chunksize: int = 10 << 20) -> Iterator[Tuple[int, pa.Table]]:
        # cf. https://github.com/huggingface/datasets/blob/2.12.0/src/datasets/packaged_modules/json/json.py
        with open(filepath, "rb") as f:
            batch_idx = 0
            block_size = max(chunksize // 32, 16 << 10)
            while True:
                batch = f.read(chunksize)
                if not batch:
                    break

                batch += f.readline()
                pa_table = pa.json.read_json(
                    io.BytesIO(batch), read_options=pa.json.ReadOptions(block_size=block_size)
                )

                yield batch_idx, pa_table
                batch_idx += 1