I’m not completely sure how your code works.
Are you defining a new rescaling size for a complete epoch?
If so, you could set the new size before the epoch is started and thus before the copies of the dataset are executed in the DataLoader loop.



 5had3z:

I’m very memory limited with only a 1070Ti so I operate at a significantly lower resolution and batch size compared to what the literature had which had a bunch of V100’s…could this also be a significant contributing factor?


Yes, the resolution as well as a different batch size might yield different results.
That being said, you might be able to change some hyperparameters to get similar results, but you would have to further experiment with the training.
Also, you could try to use torch.utils.checkpoint to trade compute for memory in order to increase the batch size or the spatial resolution.