Delete loading script

allocine.py

@@ -1,106 +0,0 @@
-"""Allocine Dataset: A Large-Scale French Movie Reviews Dataset."""
-
-
-import json
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_CITATION = """\
-@misc{blard2019allocine,
-  author = {Blard, Theophile},
-  title = {french-sentiment-analysis-with-bert},
-  year = {2020},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},
-}
-"""
-
-_DESCRIPTION = """\
- Allocine Dataset: A Large-Scale French Movie Reviews Dataset.
- This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.
- It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k).
-"""
-
-
-class AllocineConfig(datasets.BuilderConfig):
-    """BuilderConfig for Allocine."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for Allocine.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(AllocineConfig, self).__init__(**kwargs)
-
-
-class AllocineDataset(datasets.GeneratorBasedBuilder):
-    """Allocine Dataset: A Large-Scale French Movie Reviews Dataset."""
-
-    _DOWNLOAD_URL = "https://github.com/TheophileBlard/french-sentiment-analysis-with-bert/raw/master/allocine_dataset/data.tar.bz2"
-    _TRAIN_FILE = "train.jsonl"
-    _VAL_FILE = "val.jsonl"
-    _TEST_FILE = "test.jsonl"
-
-    BUILDER_CONFIGS = [
-        AllocineConfig(
-            name="allocine",
-            version=datasets.Version("1.0.0"),
-            description="Allocine Dataset: A Large-Scale French Movie Reviews Dataset",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "review": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=["neg", "pos"]),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/TheophileBlard/french-sentiment-analysis-with-bert",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="review", label_column="label")],
-        )
-
-    def _split_generators(self, dl_manager):
-        archive_path = dl_manager.download(self._DOWNLOAD_URL)
-        data_dir = "data"
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": f"{data_dir}/{self._TRAIN_FILE}",
-                    "files": dl_manager.iter_archive(archive_path),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": f"{data_dir}/{self._VAL_FILE}",
-                    "files": dl_manager.iter_archive(archive_path),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": f"{data_dir}/{self._TEST_FILE}",
-                    "files": dl_manager.iter_archive(archive_path),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, files):
-        """Generate Allocine examples."""
-        for path, file in files:
-            if path == filepath:
-                for id_, row in enumerate(file):
-                    data = json.loads(row.decode("utf-8"))
-                    review = data["review"]
-                    label = "neg" if data["polarity"] == 0 else "pos"
-                    yield id_, {"review": review, "label": label}