Delete loading script

art.py

@@ -1,116 +0,0 @@
-"""TODO(art): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(art): BibTeX citation
-_CITATION = """\
-@InProceedings{anli,
-  author = {Chandra, Bhagavatula and Ronan, Le Bras and Chaitanya, Malaviya and Keisuke, Sakaguchi and Ari, Holtzman
-    and Hannah, Rashkin and Doug, Downey and Scott, Wen-tau Yih and Yejin, Choi},
-  title = {Abductive Commonsense Reasoning},
-  year = {2020}
-}"""
-
-# TODO(art):
-_DESCRIPTION = """\
-the Abductive Natural Language Inference Dataset from AI2
-"""
-_DATA_URL = "https://storage.googleapis.com/ai2-mosaic/public/alphanli/alphanli-train-dev.zip"
-
-
-class ArtConfig(datasets.BuilderConfig):
-    """BuilderConfig for Art."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Art.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(ArtConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs)
-
-
-class Art(datasets.GeneratorBasedBuilder):
-    """TODO(art): Short description of my dataset."""
-
-    # TODO(art): Set up version.
-    VERSION = datasets.Version("0.1.0")
-    BUILDER_CONFIGS = [
-        ArtConfig(
-            name="anli",
-            description="""\
-          the Abductive Natural Language Inference Dataset from AI2.
-          """,
-        ),
-    ]
-
-    def _info(self):
-        # TODO(art): 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(
-                {
-                    "observation_1": datasets.Value("string"),
-                    "observation_2": datasets.Value("string"),
-                    "hypothesis_1": datasets.Value("string"),
-                    "hypothesis_2": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(num_classes=3)
-                    # 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://leaderboard.allenai.org/anli/submissions/get-started",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(art): 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(_DATA_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": os.path.join(dl_dir, "dev.jsonl"),
-                    "labelpath": os.path.join(dl_dir, "dev-labels.lst"),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": os.path.join(dl_dir, "train.jsonl"),
-                    "labelpath": os.path.join(dl_dir, "train-labels.lst"),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, labelpath):
-        """Yields examples."""
-        # TODO(art): Yields (key, example) tuples from the dataset
-        data = []
-        for line in open(filepath, encoding="utf-8"):
-            data.append(json.loads(line))
-        labels = []
-        with open(labelpath, encoding="utf-8") as f:
-            for word in f:
-                labels.append(word)
-        for idx, row in enumerate(data):
-            yield idx, {
-                "observation_1": row["obs1"],
-                "observation_2": row["obs2"],
-                "hypothesis_1": row["hyp1"],
-                "hypothesis_2": row["hyp2"],
-                "label": labels[idx],
-            }