# What is the point of Transforms in Pytorch when loading Dataset?

transform = transforms.Compose([
transforms.ToTensor(),
A.Normalize(CIFAR10_MEAN, CIFAR10_STD_DEV),
A.RandomCrop(height=128, width=128),])


train = datasets.CIFAR10(root=path, train=True, download=True, transform=transform)
I checked the size of train when I do no transformation, and when I do a lot of random transformations(such as random crop, random horizontal flip, etc.) and it seems like train is not getting larger(I checked using both sys.getsize() and len, and train is the same size no matter what transforms I do), so I was wondering what the point was.