Note that batchnorm layers have also affine parameters by default (affine=True).
While the weight and bias are initialized with zeros and ones, respectively, in the current master, the weight parameter was initialized with a uniform distribution up to PyTorch 1.1.0 4.
If you are not using a nightly build, you might add this to your code:
torch.manual_seed(0)
net = Net()
net.bn.bias.requires_grad=False
with torch.no_grad():
    net.bn.weight.fill_(1.)
net.bn.eval()