Delete bg-fake-news.py

bg-fake-news.py

@@ -1,98 +0,0 @@
-import json
-import textwrap
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_DESCRIPTION = "Fake news detection dataset."
-
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {A great new dataset},
-author={huggingface, Inc.
-},
-year={2020}
-}
-"""
-
-_FEATURES = datasets.Features({
-                "title": datasets.Value("string"),
-                "url": datasets.Value("string"),
-                "date_published": datasets.Value("string"),
-                "content": datasets.Value("string"),
-                "fake_news":  datasets.features.ClassLabel(names=["fake", "real"])
-            })
-
-class FakeNewsConfig(datasets.BuilderConfig):
-    """BuilderConfig for FakeNews"""
-
-    def __init__(self, data_url, citation, url, text_features, **kwargs):
-        """
-        Args:
-            text_features: `dict[string, string]`, map from the name of the feature
-        dict for each text field to the name of the column in the tsv file
-            label_column:
-            label_classes
-            **kwargs: keyword arguments forwarded to super.
-        """
-        super(FakeNewsConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs)
-        self.text_features = text_features
-        self.data_url = data_url
-        self.citation = citation
-        self.url = url
-
-
-class FakeNewsConfig(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("0.1.0")
-
-    DEFAULT_CONFIG_NAME = "default"
-
-    BUILDER_CONFIGS = [FakeNewsConfig(
-            name=DEFAULT_CONFIG_NAME,
-            description=_DESCRIPTION,
-            citation=textwrap.dedent(_CITATION),
-            text_features=_FEATURES,
-            data_url="https://gitlab.com/datasciencesociety/case_fake_news/-/blob/master/data/main_data_fake_news.csv",
-            url="https://gitlab.com/datasciencesociety/case_fake_news/-/blob/master/data/main_data_fake_news.csv",
-        )
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=_FEATURES,
-            supervised_keys=None,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager=None, config=None):
-        data_dir = dl_manager.download(self.config.data_url)
-        split_filenames = {
-            datasets.Split.TRAIN: "train.jsonl",
-            datasets.Split.VALIDATION: "dev.jsonl",
-            datasets.Split.TEST: "test.jsonl",
-        }
-        return [
-            datasets.SplitGenerator(
-                name=split,
-                gen_kwargs={
-                    "filepath": dl_manager.iter_archive(data_dir),
-                    "filename": split_filenames[split],
-                },
-            )
-            for split in split_filenames
-        ]
-
-    def _generate_examples(self, filepath=None, filename=None):
-        idx = 0
-
-        for path, file in filepath:
-            if path.endswith(filename):
-                lines = (line.decode("utf-8") for line in file)
-                for line in lines:
-                    idx += 1
-                    example = json.loads(line)
-
-                    yield idx, example