Delete loading script

wiqa.py

@@ -1,113 +0,0 @@
-"""TODO(wiqa): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(wiqa): BibTeX citation
-_CITATION = """\
-@article{wiqa,
-      author    = {Niket Tandon and Bhavana Dalvi Mishra and Keisuke Sakaguchi and Antoine Bosselut and Peter Clark}
-      title     = {WIQA: A dataset for "What if..." reasoning over procedural text},
-      journal   = {arXiv:1909.04739v1},
-      year      = {2019},
-}
-"""
-
-# TODO(wiqa):
-_DESCRIPTION = """\
-The WIQA dataset V1 has 39705 questions containing a perturbation and a possible effect in the context of a paragraph.
-The dataset is split into 29808 train questions, 6894 dev questions and 3003 test questions.
-"""
-_URL = "https://public-aristo-processes.s3-us-west-2.amazonaws.com/wiqa_dataset_no_explanation_v2/wiqa-dataset-v2-october-2019.zip"
-URl = "s3://ai2-s2-research-public/open-corpus/2020-04-10/"
-
-
-class Wiqa(datasets.GeneratorBasedBuilder):
-    """TODO(wiqa): Short description of my dataset."""
-
-    # TODO(wiqa): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(wiqa): 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(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "question_stem": datasets.Value("string"),
-                    "question_para_step": datasets.features.Sequence(datasets.Value("string")),
-                    "answer_label": datasets.Value("string"),
-                    "answer_label_as_choice": datasets.Value("string"),
-                    "choices": datasets.features.Sequence(
-                        {"text": datasets.Value("string"), "label": datasets.Value("string")}
-                    ),
-                    "metadata_question_id": datasets.Value("string"),
-                    "metadata_graph_id": datasets.Value("string"),
-                    "metadata_para_id": datasets.Value("string"),
-                    "metadata_question_type": datasets.Value("string"),
-                    "metadata_path_len": datasets.Value("int32"),
-                }
-            ),
-            # 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://allenai.org/data/wiqa",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(wiqa): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        dl_dir = dl_manager.download_and_extract(_URL)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(dl_dir, "train.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(dl_dir, "test.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(dl_dir, "dev.jsonl")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(wiqa): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-
-                yield id_, {
-                    "question_stem": data["question"]["stem"],
-                    "question_para_step": data["question"]["para_steps"],
-                    "answer_label": data["question"]["answer_label"],
-                    "answer_label_as_choice": data["question"]["answer_label_as_choice"],
-                    "choices": {
-                        "text": [choice["text"] for choice in data["question"]["choices"]],
-                        "label": [choice["label"] for choice in data["question"]["choices"]],
-                    },
-                    "metadata_question_id": data["metadata"]["ques_id"],
-                    "metadata_graph_id": data["metadata"]["graph_id"],
-                    "metadata_para_id": data["metadata"]["para_id"],
-                    "metadata_question_type": data["metadata"]["question_type"],
-                    "metadata_path_len": data["metadata"]["path_len"],
-                }