Is there any possibility to run the DataLoader fully in gpu. For instance something like DataLoader().cuda()? Is that possible. If not that would be a great addition. For instance in multigpu systems that is very handy you can have one gpu for training and another for processing the data.
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It’s not “not supported”. You can write a custom Dataset class to achieve that. Just be careful with cuda device management and interprocess communication.
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Not that I can think of. I believe that you need to use the spawn
multiprocessing spawn method for it, and be careful about the things mentioned in http://pytorch.org/docs/master/notes/multiprocessing.html
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