# coding=utf-8 # Copyright 2023 Devrim Cavusoglu and the HuggingFace Datasets Authors. # # 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. # Lint as: python3 """Wiki Long Subset.""" import json import datasets logger = datasets.logging.get_logger(__name__) _DESCRIPTION = """\ Dataset consisting of long wikipedia articles. """ _URLS = { "train": [ "train/partition_0.jsonl", "train/partition_1.jsonl", "train/partition_2.jsonl", "train/partition_3.jsonl", "train/partition_4.jsonl", "train/partition_5.jsonl", "train/partition_6.jsonl", "train/partition_7.jsonl", "train/partition_8.jsonl", "train/partition_9.jsonl", "train/partition_10.jsonl", "train/partition_11.jsonl", ], "test": "test/partition_0.jsonl", } class WikiLongDatasetConfig(datasets.BuilderConfig): """BuilderConfig for Dataset.""" def __init__(self, **kwargs): """BuilderConfig for Dataset. Args: **kwargs: keyword arguments forwarded to super. """ super(WikiLongDatasetConfig, self).__init__(**kwargs) @property def features(self): return { "id": datasets.Value("string"), "url": datasets.Value("string"), "title": datasets.Value("string"), "text": datasets.Value("string"), } class WikiLongDataset(datasets.GeneratorBasedBuilder): """WikiLongDataset Classification dataset. Version 1.0.""" BUILDER_CONFIGS = [ WikiLongDatasetConfig( version=datasets.Version("1.0.0", ""), description="Long Wikipedia Articles" ) ] BUILDER_CONFIG_CLASS = WikiLongDatasetConfig def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features(self.config.features), ) def _split_generators(self, dl_manager): data_dir = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir["train"]}), datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_dir["test"]}), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" logger.info("generating examples from = %s", filepath) if isinstance(filepath, str): filepath = [filepath] key = 0 for path in filepath: with open(path, encoding="utf-8") as data: for article in data: yield key, json.loads(article) key += 1