def METHOD_NAME():
    time_dim = Dim(Tensor("time", [batch_dim], dtype="int32"))
    in_dim = Dim(7, name="in")
    extern_data = TensorDict(
        {
            "data": Tensor("data", [batch_dim, time_dim, in_dim], dtype="float32"),
        }
    )
    class _Net(rf.Module):
        def __call__(self, x: Tensor) -> Tensor:
            return rf.reduce_mean(x, axis=(batch_dim, time_dim))
    # noinspection PyShadowingNames
    def _forward_step(*, model: _Net, extern_data: TensorDict):
        out = model(extern_data["data"])
        out.mark_as_default_output(shape=(in_dim,))
    run_model(extern_data, lambda *, epoch, step: _Net(), _forward_step)