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"""ParsiNLU Persian reading comprehension task""" |
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from __future__ import absolute_import, division, print_function |
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import json |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@article{huggingface:dataset, |
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title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian}, |
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authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others}, |
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year={2020} |
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journal = {arXiv e-prints}, |
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eprint = {2012.06154}, |
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} |
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""" |
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_DESCRIPTION = """\ |
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A Persian query paraphrasing task (paraphrase or not, given two questions). |
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The questions are partly mined using Google auto-complete, and partly translated from Quora paraphrasing dataset. |
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""" |
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_HOMEPAGE = "https://github.com/persiannlp/parsinlu/" |
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_LICENSE = "CC BY-NC-SA 4.0" |
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_URL = "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/qqp/" |
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_URLs = { |
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"train": _URL + "train.jsonl", |
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"dev": _URL + "dev.jsonl", |
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"test": _URL + "test.jsonl", |
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} |
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class ParsinluReadingComprehension(datasets.GeneratorBasedBuilder): |
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"""ParsiNLU Persian reading comprehension task.""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="parsinlu-repo", version=VERSION, description="ParsiNLU repository: query-paraphrasing" |
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), |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"q1": datasets.Value("string"), |
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"q2": datasets.Value("string"), |
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"category": datasets.Value("string"), |
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"label": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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data_dir = dl_manager.download_and_extract(_URLs) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": data_dir["train"], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": data_dir["test"], "split": "test"}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"filepath": data_dir["dev"], |
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"split": "dev", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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logger.info("generating examples from = %s", filepath) |
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with open(filepath, encoding="utf-8") as f: |
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for id_, row in enumerate(f): |
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data = json.loads(row) |
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yield id_, data |
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