Hi
As you have pointed out, resizing such large images to 244*244 would result in loss of many useful visual features because of decrease in resolution. You need these visual cues to train your network.
You need divide your images to patches of size 244*244 and train your model with batches of multiple images, like maybe 4 to 8 patch at each step. And no, dataloader only handles the collation, io and multithreaded loading of the images. İt won’t dispatch the images automatically, as far as I know.
Note that you still have an alternative though. This depends on the scale of your GPU resources, but you may be able to fit the images and your model to your GPU ram at the same time. Just as an experiment, maybe you could try to resize your images to half the size for each dimension to see what happens. İf you still get a memory error, try 1/4. İf you have enough resources, you might be able to fit your images without compromising much of the good information in your training images.