Unfortunately, these are not what I am looking for too.
def batch_norm(input, running_mean, running_var, weight=None, bias=None,
               training=False, momentum=0.1, eps=1e-5):
    f = torch._C._functions.BatchNorm(running_mean, running_var, training, momentum, eps, torch.backends.cudnn.enabled)
    return f(input, weight, bias)

Inside the batch_norm function,  torch._C._functions.BatchNorm calculates the batch_mean and batch_var first, and then use them to normalize the batch and update the running_mean and running_var. These two parameters are stored in inside the function. I am wondering is there any easy way I can access this two parameters?