Assume I have dataset with ~1.5 billion images in jpg on HDD. If I just use naive solution (get_item  loads image using default_loader from https://github.com/pytorch/vision/blob/master/torchvision/datasets/folder.py 59), one iteration by dataset takes around 13 hours. What is best approach to work with large dataset in PyTorch? Using h5py or DataBase? Or I should move data to SSD and it is only good option?