Need an opinion on this:
With GPU-based batch transforms, we’re able to parallelize the transform process, thus faster implementation. But aren’t we getting less combinations of examples in one epoch than with transforms applied at item-level. For example, with RandomErasing augmentation, I see we erase the exact same portion of whole batch, doesn’t it seem redundant? Won’t it affect the few shot learning techniques?