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Delete wikipedia_bn.py

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  1. wikipedia_bn.py +0 -75
wikipedia_bn.py DELETED
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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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- """Bengali wikipedia from 03/20/2021"""
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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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- 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(_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)