text: Title: Memory accumulation on the GPU - and a Fix!
  Body: I experienced OOM with very big datasets and realised the images were accumulating on the GPU. After a lot of digging I found that here:
  
  https://github.com/nerfstudio-project/nerfstudio/blob/702886b213a5942b64250b3c4dc632e62237a511/nerfstudio/data/datamanagers/full_images_datamanager.py#L347
  
  Because a deepcopy of the original tensor is not made, the cpu_cached images are transferred to the GPU and left there taking up memory quickly. Modifying the data dictionary does modify the underlying cached_train.
  
  Interestingly a deepcopy is performed here: https://github.com/nerfstudio-project/nerfstudio/blob/702886b213a5942b64250b3c4dc632e62237a511/nerfstudio/data/datamanagers/full_images_datamanager.py#L373
  
  I would argue that we don't want the dataset to accumulate on the GPU and a deepcopy should be added.