Someone suggested me to do a logit transform of the dataset before passing it to the model. Has anyone heard of it before?
Is the following correct in the sense of performing logit transform to the dataset? Or should I do it before any other transformation occurs.
 transform_train = tr.Compose(
            [tr.Resize((32, 32)),  # <-- should I put logit transform here?
             tr.Pad(4, padding_mode="reflect"),
             tr.RandomCrop(im_sz),
             tr.RandomHorizontalFlip(),
             tr.ToTensor(),
             tr.Normalize((.5, .5, .5), (.5, .5, .5)),
             lambda x: x + args.sigma * torch.randn_like(x),
             lambda x: -torch.log(1/x - 1)]  # <-- logit transform
        )