BatchNorm is only responsible for normalizing the activations from the previous layer, so that all the activations from the previous layer have their mean=0 and std=1.
In V1.0 doing x = self.bn1(x2) is only normalizing x2, and then passing the normalized value to x.
In V2.0 you are just not doing normalization, except that the code is same.