Delete pquad_public.py

pquad_public.py

@@ -1,94 +0,0 @@
-import json
-import datasets
-_CITATION = """\
-@article{darvishi2022pquad,
-  title={PQuAD: A Persian Question Answering Dataset},
-  author={Darvishi, Kasra and Shahbodagh, Newsha and Abbasiantaeb, Zahra and Momtazi, Saeedeh},
-  journal={arXiv preprint arXiv:2202.06219},
-  year={2022}
-}
-"""
-_DESCRIPTION = """\\\\
-ParSQuAD: Persian Question Answering Dataset based on Machine Translation of SQuAD 2.0
-"""
-_URL = "https://raw.githubusercontent.com/vassef/pquad_public/main/"
-_URLS = {
-    "train": _URL + "train_samples.json",
-    "validation":_URL + "validation_samples.json",
-    "test": _URL + "test_samples.json",
-}
-class pquad_public_Config(datasets.BuilderConfig):
-    """BuilderConfig for PQuAD."""
-    def __init__(self, **kwargs):
-        """BuilderConfig for PQuAD.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(pquad_public_Config, self).__init__(**kwargs)
-class pquad_public(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        pquad_public_Config(name="pquad_public", version=datasets.Version("1.0.0"), description="PQuAD plaint text version 2"),
-    ]
-    def _info(self):
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://github.com/vassef/pquad_public/",
-            citation=_CITATION,
-        )
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(persian_qa): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        urls_to_download = _URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
-            ]
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(persian_qa): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            print(filepath)
-            squad = json.load(f)
-            for example in squad["data"]:
-                title = example.get("title", "").strip()
-                for paragraph in example["paragraphs"]:
-                    context = paragraph["context"].strip()
-                    for qa in paragraph["qas"]:
-                        question = qa["question"].strip()
-                        id_ = qa["id"]
-                        answer_starts = [answer["answer_start"] for answer in qa["answers"]]
-                        answers = [answer["text"].strip() for answer in qa["answers"]]
-                        # Features currently used are "context", "question", and "answers".
-                        # Others are extracted here for the ease of future expansions.
-                        yield id_, {
-                            "title": title,
-                            "context": context,
-                            "question": question,
-                            "id": id_,
-                            "answers": {
-                                "answer_start": answer_starts,
-                                "text": answers,
-                            },
-                        }