Delete loading script

quartz.py

@@ -1,158 +0,0 @@
-"""TODO(quartz): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(quartz): BibTeX citation
-_CITATION = """\
-@InProceedings{quartz,
-  author = {Oyvind Tafjord and Matt Gardner and Kevin Lin and Peter Clark},
-  title = {"QUARTZ: An Open-Domain Dataset of Qualitative Relationship
-Questions"},
-  year = {"2019"},
-}
-"""
-
-# TODO(quartz):
-_DESCRIPTION = """\
-QuaRTz is a crowdsourced dataset of 3864 multiple-choice questions about open domain qualitative relationships. Each
-question is paired with one of 405 different background sentences (sometimes short paragraphs).
-The QuaRTz dataset V1 contains 3864 questions about open domain qualitative relationships. Each question is paired with
-one of 405 different background sentences (sometimes short paragraphs).
-The dataset is split into train (2696), dev (384) and test (784). A background sentence will only appear in a single split.
-"""
-
-_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/quartz-dataset-v1-aug2019.zip"
-
-
-class Quartz(datasets.GeneratorBasedBuilder):
-    """TODO(quartz): Short description of my dataset."""
-
-    # TODO(quartz): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(quartz): 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 ...
-                    "id": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "choices": datasets.features.Sequence(
-                        {"text": datasets.Value("string"), "label": datasets.Value("string")}
-                    ),
-                    "answerKey": datasets.Value("string"),
-                    "para": datasets.Value("string"),
-                    "para_id": datasets.Value("string"),
-                    "para_anno": {
-                        "effect_prop": datasets.Value("string"),
-                        "cause_dir_str": datasets.Value("string"),
-                        "effect_dir_str": datasets.Value("string"),
-                        "cause_dir_sign": datasets.Value("string"),
-                        "effect_dir_sign": datasets.Value("string"),
-                        "cause_prop": datasets.Value("string"),
-                    },
-                    "question_anno": {
-                        "more_effect_dir": datasets.Value("string"),
-                        "less_effect_dir": datasets.Value("string"),
-                        "less_cause_prop": datasets.Value("string"),
-                        "more_effect_prop": datasets.Value("string"),
-                        "less_effect_prop": datasets.Value("string"),
-                        "less_cause_dir": datasets.Value("string"),
-                    },
-                }
-            ),
-            # 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/quartz",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(quartz): 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)
-        data_dir = os.path.join(dl_dir, "quartz-dataset-v1-aug2019")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "train.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "dev.jsonl")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(quartz): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            for row in f:
-                data = json.loads(row)
-                id_ = data["id"]
-                question = data["question"]["stem"]
-                answerKey = data["answerKey"]
-                choices = data["question"]["choices"]
-                choice_text = [choice["text"] for choice in choices]
-                choice_label = [choice["label"] for choice in choices]
-                para_id = data["para_id"]
-                para = data["para"]
-                para_ano = data["para_anno"]
-                effect_prop = para_ano.get("effect_prop", "")
-                cause_dir_str = para_ano.get("cause_dir_str", "")
-                effect_dir_str = para_ano.get("effect_dir_str", "")
-                cause_dir_sign = para_ano.get("cause_dir_sign", "")
-                effect_dir_sign = para_ano.get("effect_dir_sign", "")
-                cause_prop = para_ano.get("cause_prop", "")
-                question_anno = data["question_anno"]
-                more_effect_dir = "" if not question_anno else question_anno.get("more_effect_dir", "")
-                less_effect_dir = "" if not question_anno else question_anno.get("less_effect_dir", "")
-                less_cause_prop = "" if not question_anno else question_anno.get("less_cause_prop", "")
-                more_effect_prop = "" if not question_anno else question_anno.get("more_effect_prop", "")
-                less_effect_prop = "" if not question_anno else question_anno.get("less_effect_prop", "")
-                less_cause_dir = "" if not question_anno else question_anno.get("less_effect_prop", "")
-                yield id_, {
-                    "id": id_,
-                    "question": question,
-                    "choices": {"text": choice_text, "label": choice_label},
-                    "answerKey": answerKey,
-                    "para": para,
-                    "para_id": para_id,
-                    "para_anno": {
-                        "effect_prop": effect_prop,
-                        "cause_dir_str": cause_dir_str,
-                        "effect_dir_str": effect_dir_str,
-                        "cause_dir_sign": cause_dir_sign,
-                        "effect_dir_sign": effect_dir_sign,
-                        "cause_prop": cause_prop,
-                    },
-                    "question_anno": {
-                        "more_effect_dir": more_effect_dir,
-                        "less_effect_dir": less_effect_dir,
-                        "less_cause_prop": less_cause_prop,
-                        "more_effect_prop": more_effect_prop,
-                        "less_effect_prop": less_effect_prop,
-                        "less_cause_dir": less_cause_dir,
-                    },
-                }