Hello everyone,
I am trying to develop a deep learning network and here I am planning to use Data augmentation.
In this augmentation, it adds random noise e.g. np.random.randn().
My question is,
if I use above method in pytorch, then would the dataset be updated with new random noise for every
epoch? Hence, there will be no same dataset repeatedly trained.
If not, how does data augmentation work in pytorch? Does it also use my original dataset too for training?
Thank you