# 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. """Wikipedia-Utils: Preprocessed Wikipedia Texts for NLP""" import json from typing import Dict, Iterator, List, Tuple, Union import datasets _DESCRIPTION = "Preprocessed Wikipedia texts generated with scripts in singletongue/wikipedia-utils repo." _HOMEPAGE = "https://github.com/singletongue/wikipedia-utils" _LICENSE = "The content of Wikipedia is licensed under the CC-BY-SA 3.0 and GFDL licenses." _URL_BASE = "https://github.com/singletongue/wikipedia-utils/releases/download" _URLS = { "corpus-jawiki-20230403": f"{_URL_BASE}/2023-04-03/corpus-jawiki-20230403.txt.gz", "corpus-jawiki-20230403-cirrus": f"{_URL_BASE}/2023-04-03/corpus-jawiki-20230403-cirrus.txt.gz", "corpus-jawiki-20230403-filtered-large": f"{_URL_BASE}/2023-04-03/corpus-jawiki-20230403-filtered-large.txt.gz", "paragraphs-jawiki-20230403": f"{_URL_BASE}/2023-04-03/paragraphs-jawiki-20230403.json.gz", "passages-c300-jawiki-20230403": f"{_URL_BASE}/2023-04-03/passages-c300-jawiki-20230403.json.gz", "passages-c400-jawiki-20230403": f"{_URL_BASE}/2023-04-03/passages-c400-jawiki-20230403.json.gz", "passages-para-jawiki-20230403": f"{_URL_BASE}/2023-04-03/passages-para-jawiki-20230403.json.gz", } _VERSION = datasets.Version("1.0.0") class WikipediaUtils(datasets.GeneratorBasedBuilder): """Wikipedia-Utils dataset.""" BUILDER_CONFIGS = [datasets.BuilderConfig(name=name, version=_VERSION) for name in _URLS.keys()] def _info(self) -> datasets.DatasetInfo: if self.config.name.startswith("corpus"): features = datasets.Features({"text": datasets.Value("string")}) elif self.config.name.startswith("paragraphs"): features = datasets.Features( { "id": datasets.Value("string"), "pageid": datasets.Value("int64"), "revid": datasets.Value("int64"), "paragraph_index": datasets.Value("int64"), "title": datasets.Value("string"), "section": datasets.Value("string"), "text": datasets.Value("string"), "html_tag": datasets.Value("string"), } ) elif self.config.name.startswith("passages"): features = datasets.Features( { "id": datasets.Value("int64"), "pageid": datasets.Value("int64"), "revid": datasets.Value("int64"), "title": datasets.Value("string"), "section": datasets.Value("string"), "text": datasets.Value("string"), } ) else: raise ValueError("Invalid dataset config name is specified.") return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE, ) def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: url = _URLS[self.config.name] filepath = dl_manager.download_and_extract(url) return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": filepath})] def _generate_examples(self, filepath: str) -> Iterator[Tuple[int, Dict[str, Union[int, str]]]]: if self.config.name.startswith("corpus"): with open(filepath) as f: for id_, line in enumerate(f): line = line.rstrip("\n") yield id_, {"text": line} elif self.config.name.startswith(("paragraphs", "passages")): with open(filepath) as f: for line in f: item = json.loads(line) yield item["id"], item else: raise ValueError("Invalid dataset config name is specified.")