from pathlib import Path from typing import List import datasets import pickle logger = datasets.logging.get_logger(__name__) class Fairface(datasets.GeneratorBasedBuilder): _HOMEPAGE = "https://huggingface.co/datasets/nateraw/fairface/" _URL = "https://huggingface.co/datasets/nateraw/fairface/resolve/main/" _URLS = { "train": _URL + "train.pt", "dev": _URL + "val.pt", } _DESCRIPTION = "The Fairface dataset" _CITATION = None def _info(self): return datasets.DatasetInfo( description=self._DESCRIPTION, features=datasets.Features( { 'img_bytes': datasets.Value('binary'), 'age': datasets.features.ClassLabel(names=['0-2', '3-9', '10-19', '20-29', '30-39', '40-49', '50-59', '60-69', 'more than 70']), "gender": datasets.features.ClassLabel(names=['Female', 'Male']), 'race': datasets.features.ClassLabel(names=['Black', 'East Asian', 'Indian', 'Latino_Hispanic', 'Middle Eastern', 'Southeast Asian', 'White']) } ), supervised_keys=('img_bytes', 'age'), homepage=self._HOMEPAGE, citation=self._CITATION, ) def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: downloaded_files = dl_manager.download_and_extract(self._URLS) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}) ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" logger.info("generating examples from = %s", filepath) with Path(filepath).open('rb') as f: examples = pickle.load(f) for i, ex in enumerate(examples): _id = ex.pop('_id') yield _id, ex