In documentation it says that we should use the same normalization as used for the ImageNet images, i.e.
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                  std=[0.229, 0.224, 0.225])

But what if my dataset images have a slightly different mean and std and I want to train a pretrained (on ImageNet) model on my dataset?
Should I use my own normalization or the above one from ImageNet?
Does it really matter which one to use if the differences in mean and std are small?