Delete loading script

sciq.py

@@ -1,91 +0,0 @@
-"""TODO(sciQ): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(sciQ): BibTeX citation
-_CITATION = """\
-@inproceedings{SciQ,
-    title={Crowdsourcing Multiple Choice Science Questions},
-    author={Johannes Welbl, Nelson F. Liu, Matt Gardner},
-    year={2017},
-    journal={arXiv:1707.06209v1}
-}
-"""
-
-# TODO(sciQ):
-_DESCRIPTION = """\
-The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.
-
-"""
-_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/SciQ.zip"
-
-
-class Sciq(datasets.GeneratorBasedBuilder):
-    """TODO(sciQ): Short description of my dataset."""
-
-    # TODO(sciQ): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(sciQ): 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": datasets.Value("string"),
-                    "distractor3": datasets.Value("string"),
-                    "distractor1": datasets.Value("string"),
-                    "distractor2": datasets.Value("string"),
-                    "correct_answer": datasets.Value("string"),
-                    "support": 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/sciq",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(sciQ): 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, "SciQ dataset-2 3")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "train.json")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "valid.json")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "test.json")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(sciQ): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for id_, row in enumerate(data):
-                yield id_, row