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import datasets |
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import csv |
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import os |
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import sys |
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csv.field_size_limit(sys.maxsize) |
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_DESCRIPTION = """persian_blog is a dataset consist of 700K blog posts from various websites and has types of tones. |
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this dataset can be used in different NLG tasks and as a show-case it's is used in training reformer-persian.""" |
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_PROJECT_URL = """""" |
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_CITATION = """ |
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https://saied71.github.io/RohanAiLab/, |
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author={Saied Alimoradi}, |
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year={2021} |
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} |
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""" |
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train = "train.zip" |
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test = "test.zip" |
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class persian_blog_V2(datasets.GeneratorBasedBuilder): |
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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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"text": datasets.Value("string") |
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} |
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), |
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homepage=_PROJECT_URL, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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dl_train = dl_manager.download_and_extract(train) |
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dl_test = dl_manager.download_and_extract(test) |
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train_dir = os.path.join(dl_train, "train.csv") |
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test_dir = os.path.join(dl_test, "test.csv") |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_dir}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_dir}), |
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] |
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def _generate_examples(self, filepath): |
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"""Yields examples.""" |
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with open(filepath, encoding="utf-8") as f: |
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reader = csv.reader(f) |
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for id_, row in enumerate(reader): |
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if id_ == 0: |
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continue |
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yield id_, { |
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"text": row[0] |
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} |
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