yeah but it is not doing it correct i guess. in the doc it says:

class torchvision.transforms.Normalize(mean, std)[source]
Normalize a tensor image with mean and standard deviation. Given mean: (M1,…,Mn) and std: (S1,…,Sn) for n channels, this transform will normalize each channel of the input torch.*Tensor i.e. input[channel] = (input[channel] - mean[channel]) / std[channel]

But I dont see that is doing it for each channel. I see it is doing it for the whole tensor