| """Wikipedia snippets in parquet format""" | |
| import os | |
| import pyarrow.parquet as pq | |
| import datasets | |
| logger = datasets.logging.get_logger(__name__) | |
| _CITATION = """\ | |
| @ONLINE {wikidump, | |
| author = {Wikimedia Foundation}, | |
| title = {Wikimedia Downloads}, | |
| url = {https://dumps.wikimedia.org} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| The dataset was built from the Wikipedia dump (https://dumps.wikimedia.org/). | |
| Each example contains the content of one full Wikipedia article with cleaning to strip | |
| markdown and unwanted sections (references, etc.). | |
| """ | |
| _LICENSE = ( | |
| "This work is licensed under the Creative Commons Attribution-ShareAlike " | |
| "3.0 Unported License. To view a copy of this license, visit " | |
| "http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to " | |
| "Creative Commons, PO Box 1866, Mountain View, CA 94042, USA." | |
| ) | |
| class WikipediaSnippetsStreamed(datasets.ArrowBasedBuilder): | |
| """Bengali wikipedia from 03/20/2021""" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "title": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="https://dumps.wikimedia.org", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| url = "https://storage.googleapis.com/huggingface-nlp/cache/datasets/wiki40b/en/1.1.0/wiki40b-train.parquet" | |
| downloaded_files = dl_manager.download(url) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files}), | |
| ] | |
| def _generate_tables(self, filepaths): | |
| """This function returns the examples in the raw (text) form.""" | |
| for filepath in filepaths: | |
| logger.info("generating examples from = %s", filepath) | |
| filepath_id = os.path.basename(filepath) | |
| with open(filepath, "rb") as f: | |
| pf = pq.ParquetFile(f) | |
| for i in range(pf.num_row_groups): | |
| id_ = f"{filepath_id}_{i}" | |
| yield id_, pf.read_row_group(i) | |