def METHOD_NAME(self, msg):
    frame = CondIndepStackFrame(
        self.name, self.dim, self.subsample_size, self.counter
    )
    frame.full_size = self.size  # Used for param initialization.
    msg["cond_indep_stack"] = (frame,) + msg["cond_indep_stack"]
    if isinstance(self.size, torch.Tensor) or isinstance(
        self.subsample_size, torch.Tensor
    ):
        if not isinstance(msg["scale"], torch.Tensor):
            with ignore_jit_warnings():
                msg["scale"] = torch.tensor(msg["scale"])
    msg["scale"] = msg["scale"] * self.size / self.subsample_size