import datasets import pickle import json class EmbeddingsDatasetConfig(datasets.BuilderConfig): def __init__(self, image_base_m, embeddingSize, **kwargs): super(EmbeddingsDatasetConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) self.data_urls = "" self.image_base_m = image_base_m self.embeddingSize = embeddingSize class ImageCaptionsEmbeddings(datasets.GeneratorBasedBuilder): BUILDER_CONFIGS = [ EmbeddingsDatasetConfig( name="Vit-B-32", image_base_m="Vit-B-32-2", embeddingSize=512, ), ] DEFAULT_CONFIG_NAME = "Vit-B-32" def _info(self): return datasets.DatasetInfo( description='test', features=datasets.Features( { "id": datasets.Value('string'), "embedding": datasets.Array2D((1, self.config.embeddingSize), 'float32') } ), ) def _split_generators(self, dl_manager): urls_to_download = self.config.data_urls downloaded_files = dl_manager.download_and_extract(urls_to_download) downloaded_files = ["/home/think3/Desktop/1. MSCOCO_captions_dataset_edited/dataset_test_jsonl/en_captions_json.jsonl"] return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={ "data_files": downloaded_files, }) ] def _generate_examples(self, data_files): for data_file in data_files: with open(data_file, "r") as input_file: for line in input_file: json_data = json.loads(line) yield json_data["id"], { "id": json_data["id"], "embedding": json_data["embedding"], }