You could create a custom transformation:
class AddGaussianNoise(object):
    def __init__(self, mean=0., std=1.):
        self.std = std
        self.mean = mean
        
    def __call__(self, tensor):
        return tensor + torch.randn(tensor.size()) * self.std + self.mean
    
    def __repr__(self):
        return self.__class__.__name__ + '(mean={0}, std={1})'.format(self.mean, self.std)

and just add it to transforms.Compose:
transform=transforms.Compose([
    transforms.ToTensor(),
    transforms.Normalize((0.1307,), (0.3081,)),
    AddGaussianNoise(0., 1.)
])