|
""" 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 = {} |
|
|
|
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"] |
|
} |
|
|
|
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, |
|
) |