Delete loading script

squad_v2.py

@@ -1,133 +0,0 @@
-"""TODO(squad_v2): Add a description here."""
-
-
-import json
-
-import datasets
-from datasets.tasks import QuestionAnsweringExtractive
-
-
-# TODO(squad_v2): BibTeX citation
-_CITATION = """\
-@article{2016arXiv160605250R,
-       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},
-                 Konstantin and {Liang}, Percy},
-        title = "{SQuAD: 100,000+ Questions for Machine Comprehension of Text}",
-      journal = {arXiv e-prints},
-         year = 2016,
-          eid = {arXiv:1606.05250},
-        pages = {arXiv:1606.05250},
-archivePrefix = {arXiv},
-       eprint = {1606.05250},
-}
-"""
-
-_DESCRIPTION = """\
-combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers
- to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but
- also determine when no answer is supported by the paragraph and abstain from answering.
-"""
-
-_URL = "https://rajpurkar.github.io/SQuAD-explorer/dataset/"
-_URLS = {
-    "train": _URL + "train-v2.0.json",
-    "dev": _URL + "dev-v2.0.json",
-}
-
-
-class SquadV2Config(datasets.BuilderConfig):
-    """BuilderConfig for SQUAD."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for SQUADV2.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(SquadV2Config, self).__init__(**kwargs)
-
-
-class SquadV2(datasets.GeneratorBasedBuilder):
-    """TODO(squad_v2): Short description of my dataset."""
-
-    # TODO(squad_v2): Set up version.
-    BUILDER_CONFIGS = [
-        SquadV2Config(name="squad_v2", version=datasets.Version("2.0.0"), description="SQuAD plaint text version 2"),
-    ]
-
-    def _info(self):
-        # TODO(squad_v2): 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"),
-                    "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"),
-                        }
-                    ),
-                    # 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://rajpurkar.github.io/SQuAD-explorer/",
-            citation=_CITATION,
-            task_templates=[
-                QuestionAnsweringExtractive(
-                    question_column="question", context_column="context", answers_column="answers"
-                )
-            ],
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(squad_v2): 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["dev"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(squad_v2): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            squad = json.load(f)
-            for example in squad["data"]:
-                title = example.get("title", "")
-                for paragraph in example["paragraphs"]:
-                    context = paragraph["context"]  # do not strip leading blank spaces GH-2585
-                    for qa in paragraph["qas"]:
-                        question = qa["question"]
-                        id_ = qa["id"]
-
-                        answer_starts = [answer["answer_start"] for answer in qa["answers"]]
-                        answers = [answer["text"] 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,
-                            },
-                        }