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from datasets import load_dataset_builder, DatasetInfo, DownloadConfig, GeneratorBasedBuilder, datasets |
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class CustomSQuADFormatDataset(GeneratorBasedBuilder): |
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"""A custom dataset similar to SQuAD but tailored for 'ArabicaQA' hosted on Hugging Face.""" |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="ArabicaQA", version=VERSION, description="Custom dataset similar to SQuAD format.") |
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] |
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def _info(self): |
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return DatasetInfo( |
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description="This dataset is formatted similarly to the SQuAD dataset.", |
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features=datasets.Features( |
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{ |
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"id": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"context": datasets.Value("string"), |
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"question": datasets.Value("string"), |
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"answers": datasets.features.Sequence( |
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{ |
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"text": datasets.Value("string"), |
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"answer_start": datasets.Value("int32"), |
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} |
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), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://huggingface.co/datasets/abdoelsayed/ArabicaQA", |
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citation="", |
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) |
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def _split_generators(self, dl_manager: DownloadConfig): |
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urls_to_download = { |
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"train": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/train.json", |
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"dev": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/val.json", |
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"test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json" |
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} |
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downloaded_files = dl_manager.download(urls_to_download) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["test"]}), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, encoding="utf-8") as f: |
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squad_data = json.load(f)["data"] |
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for article in squad_data: |
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title = article.get("title", "") |
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for paragraph in article["paragraphs"]: |
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context = paragraph["context"] |
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for qa in paragraph["qas"]: |
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id_ = qa["id"] |
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question = qa["question"] |
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answers = [{"text": answer["text"], "answer_start": answer["answer_start"]} for answer in qa.get("answers", [])] |
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yield id_, { |
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"title": title, |
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"context": context, |
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"question": question, |
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"answers": answers, |
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} |
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