FYI, I made this in the end:
class RandNoisyTransform(Transform):
order = 100 # After Normalize
def __init__(self, noise_factor = 0.5):
self.noise_factor = noise_factor
def __call__(self, b, **kwargs):
x,y = b
return x + self.noise_factor * torch.randn(x.shape), y