Delete loading script

tweet_topic_multi.py

@@ -1,102 +0,0 @@
-""" TweetTopic Dataset """
-import json
-from itertools import chain
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-_DESCRIPTION = """[TweetTopic](https://arxiv.org/abs/2209.09824)"""
-
-_VERSION = "1.0.4"
-_CITATION = """
-@inproceedings{dimosthenis-etal-2022-twitter,
-    title = "{T}witter {T}opic {C}lassification",
-    author = "Antypas, Dimosthenis  and
-    Ushio, Asahi  and
-    Camacho-Collados, Jose  and
-    Neves, Leonardo  and
-    Silva, Vitor  and
-    Barbieri, Francesco",
-    booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
-    month = oct,
-    year = "2022",
-    address = "Gyeongju, Republic of Korea",
-    publisher = "International Committee on Computational Linguistics"
-}
-"""
-_HOME_PAGE = "https://cardiffnlp.github.io"
-_LABEL_TYPE = "multi"
-_NAME = f"tweet_topic_{_LABEL_TYPE}"
-_URL = f'https://huggingface.co/datasets/cardiffnlp/{_NAME}/raw/main/dataset'
-_URLS = {
-    f"{str(datasets.Split.TEST)}_2020": [f'{_URL}/split_temporal/test_2020.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TEST)}_2021": [f'{_URL}/split_temporal/test_2021.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_2020": [f'{_URL}/split_temporal/train_2020.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_2021": [f'{_URL}/split_temporal/train_2021.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_all": [f'{_URL}/split_temporal/train_2020.{_LABEL_TYPE}.json', f'{_URL}/split_temporal/train_2021.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.VALIDATION)}_2020": [f'{_URL}/split_temporal/validation_2020.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.VALIDATION)}_2021": [f'{_URL}/split_temporal/validation_2021.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_random": [f'{_URL}/split_random/train_random.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.VALIDATION)}_random": [f'{_URL}/split_random/validation_random.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TEST)}_coling2022_random": [f'{_URL}/split_coling2022_random/test_random.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_coling2022_random": [f'{_URL}/split_coling2022_random/train_random.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TEST)}_coling2022": [f'{_URL}/split_coling2022_temporal/test_2021.{_LABEL_TYPE}.json'],
-    f"{str(datasets.Split.TRAIN)}_coling2022": [f'{_URL}/split_coling2022_temporal/train_2020.{_LABEL_TYPE}.json'],
-}
-
-
-class TweetTopicSingleConfig(datasets.BuilderConfig):
-    """BuilderConfig"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(TweetTopicSingleConfig, self).__init__(**kwargs)
-
-
-class TweetTopicSingle(datasets.GeneratorBasedBuilder):
-    """Dataset."""
-
-    BUILDER_CONFIGS = [
-        TweetTopicSingleConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
-    ]
-
-    def _split_generators(self, dl_manager):
-        downloaded_file = dl_manager.download_and_extract(_URLS)
-        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[i]}) for i in _URLS.keys()]
-
-    def _generate_examples(self, filepaths):
-        _key = 0
-        for filepath in filepaths:
-            logger.info(f"generating examples from = {filepath}")
-            with open(filepath, encoding="utf-8") as f:
-                _list = [i for i in f.read().split('\n') if len(i) > 0]
-                for i in _list:
-                    data = json.loads(i)
-                    yield _key, data
-                    _key += 1
-
-    def _info(self):
-        names = [
-                "arts_&_culture", "business_&_entrepreneurs", "celebrity_&_pop_culture", "diaries_&_daily_life", "family",
-                "fashion_&_style", "film_tv_&_video", "fitness_&_health", "food_&_dining", "gaming",
-                "learning_&_educational", "music", "news_&_social_concern", "other_hobbies", "relationships",
-                "science_&_technology", "sports", "travel_&_adventure", "youth_&_student_life"
-            ]
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "date": datasets.Value("string"),
-                    "label": datasets.Sequence(datasets.features.ClassLabel(names=names)),
-                    "label_name": datasets.Sequence(datasets.Value("string")),
-                    "id": datasets.Value("string")
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOME_PAGE,
-            citation=_CITATION,
-        )