lhoestq
HF staff
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+ """Bengali wikipedia from 03/20/2021"""
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+
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+ import os
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+ import pyarrow.parquet as pq
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+
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+ import datasets
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+
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+
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+ logger = datasets.logging.get_logger(__name__)
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+
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+
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+ _CITATION = """\
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+ @ONLINE {wikidump,
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+ author = {Wikimedia Foundation},
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+ title = {Wikimedia Downloads},
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+ url = {https://dumps.wikimedia.org}
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+ }
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+ """
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+
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+ _DESCRIPTION = """\
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+ Bengali Wikipedia from the dump of 03/20/2021.
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+ The data was processed using the huggingface datasets wikipedia script early april 2021.
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+ The dataset was built from the Wikipedia dump (https://dumps.wikimedia.org/).
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+ Each example contains the content of one full Wikipedia article with cleaning to strip
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+ markdown and unwanted sections (references, etc.).
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+ """
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+
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+ _LICENSE = (
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+ "This work is licensed under the Creative Commons Attribution-ShareAlike "
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+ "3.0 Unported License. To view a copy of this license, visit "
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+ "http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to "
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+ "Creative Commons, PO Box 1866, Mountain View, CA 94042, USA."
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+ )
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+
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+ _N_SHARDS = 10
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+
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+ _URLS = {
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+ "train": [f"data/20210320/shard-{i:05d}-of-{_N_SHARDS:05d}.parquet" for i in range(_N_SHARDS)],
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+ }
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+
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+
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+ class WikipediaBn(datasets.ArrowBasedBuilder):
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+ """SQUAD: The Stanford Question Answering Dataset. Version 1.1."""
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "title": datasets.Value("string"),
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+ "text": datasets.Value("string"),
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+ }
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+ ),
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+ # No default supervised_keys (as we have to pass both question
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+ # and context as input).
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+ supervised_keys=None,
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+ homepage="https://dumps.wikimedia.org",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ downloaded_files = dl_manager.download_and_extract(_URLS)
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+
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files["train"]}),
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+ ]
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+
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+ def _generate_tables(self, filepaths):
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+ """This function returns the examples in the raw (text) form."""
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+ for filepath in filepaths:
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+ logger.info("generating examples from = %s", filepath)
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+ filepath_id = os.path.basename(filepath)
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+ with open(filepath, "rb") as f:
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+ pf = pq.ParquetFile(f)
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+ for i in range(pf.num_row_groups):
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+ id_ = f"{filepath_id}_{i}"
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+ yield id_, pf.read_row_group(i)