MiniFastai

Databunch(train_loader::Flux.Data.DataLoader,val_loader::Flux.Data.DataLoader)

Two dataloaders, one for the train set and one for the validation set.

normalize(x,m,s)

Substract scalar m from array x and rescale by scalar s.

normalize_imgs(imgs, labels; is_train=true, m=0, s=1)

Take a onehot encoding of the labels. If is_train=true, compute the mean and std of the images and normalize them. Return the normalized images and the mean and std computed. Otherwise, normalize the imgs with m and s. Should be used with is_train=true on the train set and with is_train=false otherwise with the parameters m and s computed on the training set.