Delete loading script

xquad.py

@@ -1,131 +0,0 @@
-"""TODO(xquad): Add a description here."""
-
-
-import json
-
-import datasets
-from datasets.tasks import QuestionAnsweringExtractive
-
-
-_CITATION = """\
-@article{Artetxe:etal:2019,
-      author    = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
-      title     = {On the cross-lingual transferability of monolingual representations},
-      journal   = {CoRR},
-      volume    = {abs/1910.11856},
-      year      = {2019},
-      archivePrefix = {arXiv},
-      eprint    = {1910.11856}
-}
-"""
-
-_DESCRIPTION = """\
-XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
-performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
-of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translations into ten languages: Spanish, German,
-Greek, Russian, Turkish, Arabic, Vietnamese, Thai, Chinese, Hindi and Romanian. Consequently, the dataset is entirely parallel
-across 12 languages.
-"""
-
-_URL = "https://github.com/deepmind/xquad/raw/master/"
-_LANG = ["ar", "de", "zh", "vi", "en", "es", "hi", "el", "th", "tr", "ru", "ro"]
-
-
-class XquadConfig(datasets.BuilderConfig):
-
-    """BuilderConfig for Xquad"""
-
-    def __init__(self, lang, **kwargs):
-        """
-
-        Args:
-            lang: string, language for the input text
-            **kwargs: keyword arguments forwarded to super.
-        """
-        super(XquadConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
-        self.lang = lang
-
-
-class Xquad(datasets.GeneratorBasedBuilder):
-    """TODO(xquad): Short description of my dataset."""
-
-    # TODO(xquad): Set up version.
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [XquadConfig(name=f"xquad.{lang}", description=_DESCRIPTION, lang=lang) for lang in _LANG]
-
-    def _info(self):
-        # TODO(xquad): Specifies the datasets.DatasetInfo object
-        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"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ),
-                    # These are the features of your dataset like images, labels ...
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://github.com/deepmind/xquad",
-            citation=_CITATION,
-            task_templates=[
-                QuestionAnsweringExtractive(
-                    question_column="question", context_column="context", answers_column="answers"
-                )
-            ],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(xquad): 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 = {lang: _URL + f"xquad.{lang}.json" for lang in _LANG}
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": downloaded_files[self.config.lang]},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(xquad): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            xquad = json.load(f)
-            id_ = 0
-            for article in xquad["data"]:
-                for paragraph in article["paragraphs"]:
-                    context = paragraph["context"].strip()
-                    for qa in paragraph["qas"]:
-                        question = qa["question"].strip()
-                        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_, {
-                            "context": context,
-                            "question": question,
-                            "id": qa["id"],
-                            "answers": {
-                                "answer_start": answer_starts,
-                                "text": answers,
-                            },
-                        }
-                        id_ += 1