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At what points during training do you need to change the dataset parameters? if it's at the start of every epoch, this flag should work for you: https://pytorch-lightning.readthedocs.io/en/latest/common/trainer.html#reload-dataloaders-every-epoch If you're using a lightning datamodule, you can re-initialize the dataset and then create a new dataloader across training/validation/test |
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I would like to change dataset parameters(e.g. other augmentations). What is the pl way to reinit dataset and dataloader with new parameters?
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