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import os |
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import json |
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import datasets |
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from datasets import DownloadManager |
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_URL = "data.zip" |
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class NewsHeadDataset(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo( |
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description = "newshead multi document summarisation dataset", |
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features = datasets.Features( |
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{ |
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"documents": datasets.Value("string"), |
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"summary": datasets.Value("string") |
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} |
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) |
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) |
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def _split_generators(self, dl_manager: DownloadManager): |
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data_dir = dl_manager.download_and_extract(_URL) |
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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": os.path.join(data_dir, "train.jsonl"), |
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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.VALIDATION, |
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gen_kwargs = { |
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"filepath": os.path.join(data_dir, "validation.jsonl"), |
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"split": "validation" |
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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 = { |
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"filepath": os.path.join(data_dir, "validation.jsonl"), |
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"split": "test" |
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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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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_, { |
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"documents": data["text"], |
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"summary": data["summary"] |
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} |
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