Hello Everyone,
New convert to pytorch here. I’m trying to implement the paper ‘unsupervised learning by predicting noise’ by Bojanowski et al. To do a sanity test i’m testing on the cifar10 dataset. I had two questions regarding the dataloader from torchvision.datasets.
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is it possible to shuffle the dataset once and then keep it constant till such time that a shuffle command is called again (as opposed to shuffling every epoch).
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is it possible to get the index of the instances in the batch (this would allow me to associate it with a noise vector).
Or would it be better to write my own dataloader?
Thanks in anticipation.