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import datasets |
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from glob import glob |
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import json |
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import zipfile |
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from random import shuffle |
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_DESCRIPTION = """\ |
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Masader is the largest public catalogue for Arabic NLP datasets, which consists of more than 200 datasets annotated with 25 attributes. |
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""" |
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_CITATION = """\ |
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@misc{alyafeai2021masader, |
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title={Masader: Metadata Sourcing for Arabic Text and Speech Data Resources}, |
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author={Zaid Alyafeai and Maraim Masoud and Mustafa Ghaleb and Maged S. Al-shaibani}, |
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year={2021}, |
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eprint={2110.06744}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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""" |
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class MasaderConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Masader.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for MetRec. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(MasaderConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
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class Masader(datasets.GeneratorBasedBuilder): |
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"""Masaderdataset.""" |
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BUILDER_CONFIGS = [ |
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MasaderConfig( |
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name="plain_text", |
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description="Plain text", |
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) |
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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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'Name': datasets.Value("string"), |
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'Subsets': [{'Name':datasets.Value("string"), |
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'Dialect':datasets.Value("string") , |
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'Volume':datasets.Value("string") , |
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'Unit':datasets.Value("string")}], |
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'HF Link': datasets.Value("string"), |
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'Link': datasets.Value("string"), |
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'License': datasets.Value("string"), |
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'Year': datasets.Value("int32"), |
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'Language': datasets.Value("string"), |
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'Dialect': datasets.Value("string"), |
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'Domain': datasets.Value("string"), |
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'Form': datasets.Value("string"), |
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'Collection Style': datasets.Value("string"), |
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'Description': datasets.Value("string"), |
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'Volume': datasets.Value("string"), |
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'Unit': datasets.Value("string"), |
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'Ethical Risks': datasets.Value("string"), |
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'Provider': datasets.Value("string"), |
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'Derived From': datasets.Value("string"), |
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'Paper Title': datasets.Value("string"), |
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'Paper Link': datasets.Value("string"), |
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'Script': datasets.Value("string"), |
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'Tokenized': datasets.Value("string"), |
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'Host': datasets.Value("string"), |
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'Access': datasets.Value("string"), |
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'Cost': datasets.Value("string"), |
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'Test Split': datasets.Value("string"), |
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'Tasks': datasets.Value("string"), |
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'Venue Title': datasets.Value("string"), |
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'Citations': datasets.Value("string"), |
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'Venue Type': datasets.Value("string"), |
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'Venue Name': datasets.Value("string"), |
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'Authors': datasets.Value("string"), |
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'Affiliations': datasets.Value("string"), |
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'Abstract': datasets.Value("string"), |
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'Added By': datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://github.com/arbml/Masader", |
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citation=_CITATION,) |
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def extract_all(self, dir): |
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zip_files = glob(dir+'/**/**.zip', recursive=True) |
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for file in zip_files: |
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with zipfile.ZipFile(file) as item: |
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item.extractall('/'.join(file.split('/')[:-1])) |
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def _split_generators(self, dl_manager): |
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url = ['https://github.com/ARBML/masader/archive/main.zip'] |
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downloaded_files = dl_manager.download_and_extract(url) |
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self.extract_all(downloaded_files[0]) |
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all_files = sorted(glob(downloaded_files[0]+'/masader-main/datasets/**.json')) |
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shuffle(all_files) |
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return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths':{'inputs':all_files} })] |
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def _generate_examples(self, filepaths): |
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for idx,filepath in enumerate(filepaths['inputs']): |
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with open(filepath, 'r') as f: |
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data = json.load(f) |
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yield idx, data |