# coding=utf-8 # 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. """The Open WebText Corpus""" import re import datasets trust_remote_code=True _CITATION = """\ @misc{Gokaslan2019OpenWeb, title={OpenWebText Corpus}, author={Aaron Gokaslan*, Vanya Cohen*, Ellie Pavlick, Stefanie Tellex}, howpublished{\\url{http://Skylion007.github.io/OpenWebTextCorpus}}, year={2019} } """ _DESCRIPTION = """\ An open-source replication of the WebText dataset from OpenAI. """ _N_DATA_FILES = 21 _DATA_FILES = ["subsets/urlsf_subset{:02d}.tar".format(i) for i in range(_N_DATA_FILES)] class Openwebtext(datasets.GeneratorBasedBuilder): """The Open WebText dataset.""" BUILDER_CONFIGS = [ datasets.BuilderConfig( name="plain_text", description="Plain text", version=datasets.Version("1.0.0"), ) ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features({"text": datasets.Value("string")}), homepage="https://skylion007.github.io/OpenWebTextCorpus/", citation=_CITATION, ) def _split_generators(self, dl_manager): archives = dl_manager.download(_DATA_FILES) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ "archive_iterators": [ dl_manager.iter_archive(archive) for archive in archives ], "iter_archive": dl_manager.iter_archive }), ] def _generate_examples(self, archive_iterators, iter_archive): """Yields examples.""" for archive_iterator in archive_iterators: for xz_filepath, xz_f in archive_iterator: if not xz_filepath.endswith(".xz"): continue for txt_filepath, txt_f in iter_archive(xz_f): if not txt_filepath.endswith(".txt"): continue idx = f"{xz_filepath}/{txt_filepath}" yield idx, {"text": re.sub("\n\n\n+", "\n\n", txt_f.read().decode("utf-8")).strip()}