Delete tweet_topic_multilingual.py

tweet_topic_multilingual.py

@@ -1,173 +0,0 @@
-""" TweetTopicMultilingual Dataset """
-import json
-from typing import List
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-_DESCRIPTION = """[TweetTopicMultilingual](TBA)"""
-_VERSION = "0.0.91"
-_CITATION = """TBA"""
-_HOME_PAGE = "https://cardiffnlp.github.io"
-_NAME = "tweet_topic_multilingual"
-_ROOT_URL = f"https://huggingface.co/datasets/cardiffnlp/{_NAME}/resolve/main/dataset"
-_LANGUAGES = ["en", "es", "ja", "gr"]
-_CLASS_MAPPING = {
-    "en": [
-        "Arts & Culture",
-        "Business & Entrepreneurs",
-        "Celebrity & Pop Culture",
-        "Diaries & Daily Life",
-        "Family",
-        "Fashion & Style",
-        "Film, TV & Video",
-        "Fitness & Health",
-        "Food & Dining",
-        "Learning & Educational",
-        "News & Social Concern",
-        "Relationships",
-        "Science & Technology",
-        "Youth & Student Life",
-        "Music",
-        "Gaming",
-        "Sports",
-        "Travel & Adventure",
-        "Other Hobbies"
-    ],
-    "gr": [
-        "Τέχνες & Πολιτισμός",
-        "Επιχειρήσεις & Επιχειρηματίες",
-        "Διασημότητες & Ποπ κουλτούρα",
-        "Ημερολόγια & Καθημερινή ζωή",
-        "Οικογένεια",
-        "Μόδα & Στυλ",
-        "Ταινίες, τηλεόραση & βίντεο",
-        "Γυμναστική & Υεία",
-        "Φαγητό & Δείπνο",
-        "Μάθηση & Εκπαίδευση",
-        "Ειδήσεις & Κοινωνία",
-        "Σχέσεις",
-        "Επιστήμη & Τεχνολογία",
-        "Νεανική & Φοιτητική ζωή",
-        "Μουσική",
-        "Παιχνίδια",
-        "Αθλητισμός",
-        "Ταξίδια & Περιπέτεια",
-        "Άλλα χόμπι"
-    ],
-    "es": [
-        "Arte y cultura",
-        "Negocios y emprendedores",
-        "Celebridades y cultura pop",
-        "Diarios y vida diaria",
-        "Familia",
-        "Moda y estilo",
-        "Cine, televisión y video",
-        "Estado físico y salud",
-        "Comida y comedor",
-        "Aprendizaje y educación",
-        "Noticias e interés social",
-        "Relaciones",
-        "Ciencia y Tecnología",
-        "Juventud y Vida Estudiantil",
-        "Música",
-        "Juegos",
-        "Deportes",
-        "Viajes y aventuras",
-        "Otros pasatiempos"
-    ],
-    "ja": [
-        "アート&カルチャー",
-        "ビジネス",
-        "芸能",
-        "日常",
-        "家族",
-        "ファッション",
-        "映画&ラジオ",
-        "フィットネス&健康",
-        "料理",
-        "教育関連",
-        "社会",
-        "人間関係",
-        "サイエンス",
-        "学校",
-        "音楽",
-        "ゲーム",
-        "スポーツ",
-        "旅行",
-        "その他"
-    ]
-}
-
-_URL = {}
-# plain split
-for lan in _LANGUAGES:
-    _URL[lan] = {split: [f"{_ROOT_URL}/{lan}/{lan}_{split}.jsonl"] for split in ["train", "test", "validation"]}
-_URL["en_2022"] = {split: [f"{_ROOT_URL}/en_2022/{split}.jsonl"] for split in ["train", "validation"]}
-_URL["mix"] = {
-    split: [f"{_ROOT_URL}/{lan}/{lan}_{split}.jsonl" for lan in _LANGUAGES] for split in ["train", "validation"]
-}
-_URL["mix_2022"] = {
-    split: [f"{_ROOT_URL}/{lan}/{lan}_{split}.jsonl" for lan in _LANGUAGES] + [f"{_ROOT_URL}/en_2022/{split}.jsonl"]
-    for split in ["train", "validation"]
-}
-# cross validation
-for lan in _LANGUAGES:
-    _URL.update({
-        f"{lan}_cross_validation_{n}": {
-            split: [f"{_ROOT_URL}/{lan}/cross_validation/{lan}_{split}_{n}.jsonl"]
-            for split in ["train", "test", "validation"]
-        } for n in range(5)
-    })
-
-
-class Config(datasets.BuilderConfig):
-    """BuilderConfig"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(Config, self).__init__(**kwargs)
-
-
-class TweetTopicMultilingual(datasets.GeneratorBasedBuilder):
-    """Dataset."""
-
-    BUILDER_CONFIGS = [
-        Config(name=i, version=datasets.Version(_VERSION), description=_DESCRIPTION) for i in _URL.keys()
-    ]
-
-    def _split_generators(self, dl_manager):
-        downloaded_file = dl_manager.download_and_extract(_URL[self.config.name])
-        splits = _URL[self.config.name].keys()
-        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepath": downloaded_file[i]}) for i in splits]
-
-    def _generate_examples(self, filepath: List[str]):
-        _key = 0
-        for _file in filepath:
-            logger.info("generating examples from = %s", _file)
-            with open(_file, encoding="utf-8") as f:
-                _list = [json.loads(i) for i in f.read().split("\n") if len(i) > 0]
-                for i in _list:
-                    yield _key, i
-                    _key += 1
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "label_name_flatten": datasets.Value("string"),
-                    "label": datasets.Sequence(datasets.features.ClassLabel(names=_CLASS_MAPPING["en"])),
-                    "label_name": datasets.Sequence(datasets.Value("string"))
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOME_PAGE,
-            citation=_CITATION,
-        )