data loader

Data loading is where training pipelines quietly bottleneck. The signal is a correct shuffle-then-batch iterator plus knowing why prefetching and parallel loading keep the GPU fed.

A build-it-yourself check on distributed input pipelines. What matters is partitioning data across workers with no overlap and no gaps, epoch-consistent shuffling with a shared seed, and handling the uneven-last-batch problem. The code follows.