Instead of inventing a new format, WebDataset represents large datasets as collections of POSIX tar archive files consisting of the original data files. The WebDataset library can use such tar archives directly for training, without the need for unpacking or local storage.
WebDataset scales perfectly from small, local datasets to petascale datasets and training on hundreds of GPUs and allows data to be stored on local disk, on web servers, or dedicated file servers. For container-based training, WebDataset eliminates the need for volume plugins or node-local storage. As an additional benefit, datasets need not be unpacked prior to training, simplifying the distribution and use of research data.