Okay got it. Here’s something that’s really puzzling to me though. 1 sample of my DataLoader appears to have ~250Mb (when I first load 1 sample into the GPU). But oddly, if i increment my batch size to 4, I get this error
RuntimeError: CUDA out of memory. Tried to allocate 7.41 GiB (GPU 0; 11.17 GiB total capacity; 8.34 GiB already allocated; 2.28 GiB free; 8.60 GiB reserved in total by PyTorch)

Which is really odd, does this mean my data object is actually larger? In this instance, 7.41/4 = 1.8 Gb?