Changing Scale / Range of Image Data from 0-1 to -1-1

Is there an easy way (via transforms or otherwise) to scale image data from the range of 0 to 1 (the default) to -1 to 1?

In pure pytorch, using functional transforms, that would look something like this:

import torchvision.transforms.functional as TF
from PIL import Image
image ='path_to_image.png')
image_tensor = TF.to_tensor(TF.resize(image, 256)) * 2 - 1

I think adding a custom transform could do the trick. Something like this maybe?

def rescale(x:TensorImage): 
    return (x - x.min()) / (x.max() - x.min())  

Then add this as batch_tfms to the DataLoader. Maybe the convenience functions like, ImageDataLoaders.from_XXX will not work with this and you have to build a DataBlock first, then creating DataLoaders from it.