import datasets _CITATION = """\ @InProceedings{huggingface:dataset, title = {Unsplash 25K Photos}, author={James Briggs}, year={2022} } """ _DESCRIPTION = """\ This is a dataset that streams photos data from the Unsplash 25K servers. """ _HOMEPAGE = "https://github.com/unsplash/datasets/" _LICENSE = "" _URL = "https://unsplash.com/data/lite/latest" class Unsplash(datasets.GeneratorBasedBuilder): """The Unsplash 25K dataset for photos""" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "imdb_id": datasets.Value("string"), "movie_id": datasets.Value("int32"), "user_id": datasets.Value("int32"), "rating": datasets.Value("float32"), "title": datasets.Value("string"), "year": datasets.Value("int32"), } ), supervised_keys=None, homepage="https://grouplens.org/datasets/movielens/", citation=_CITATION, ) def _split_generators(self, dl_manager): new_url = dl_manager.download_and_extract(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": new_url+"/photos.tsv000"} ), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" with open(filepath, "r") as f: id_ = 0 for line in f: if id_ == 0: cols = line.split("\t") id_ += 1 else: values = line.split("\t") print(id_, {cols[i]: values[i] for i in range(len(cols))}) id_ += 1 if id_ > 5: break