# 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. # Lint as: python3 import json import datasets from dataclasses import dataclass _CITATION = ''' ''' languages2filesize = { 'ar': 32, 'de': 150, 'en': 352, 'es': 102, 'fr': 134, 'hi': 5, 'it': 83, 'ja': 47, 'ko': 13, 'simple': 5, 'zh': 23 } _DESCRIPTION = 'dataset load script' _DATASET_URLS = { lang: [f'https://huggingface.co/datasets/Cohere/wikipedia-22-12/resolve/main/{lang}/{str(i).zfill(3)}.jsonl.gz' for i in range(n)] for lang, n in languages2filesize.items() } class WikiCorpus(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ datasets.BuilderConfig( version=datasets.Version('1.0.0'), name=lang, description=f'Wiki dataset in language {lang}.' ) for lang in languages2filesize ] def _info(self): features = datasets.Features({ 'id': datasets.Value('int32'), 'title': datasets.Value('string'), 'text': datasets.Value('string'), 'url': datasets.Value('string'), 'wiki_id': datasets.Value('int32'), 'views': datasets.Value('float32'), 'paragraph_id': datasets.Value('int32'), 'langs': datasets.Value('int32'), #'emb': datasets.Sequence(datasets.Value("float32")) }) return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # This defines the different columns of the dataset and their types features=features, # Here we define them above because they are different between the two configurations supervised_keys=None, # Homepage of the dataset for documentation homepage='https://www.cohere.ai', # License for the dataset if available license='', # Citation for the dataset citation=_CITATION, ) def _split_generators(self, dl_manager): lang = self.config.name downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang]) splits = [ datasets.SplitGenerator( name='train', gen_kwargs={ 'filepaths': downloaded_files, }, ), ] return splits def _generate_examples(self, filepaths): for filepath in filepaths: with open(filepath, encoding="utf-8") as f: for line in f: data = json.loads(line) yield data['id'], data