Sequentials _maybe_rebuild does not make sense

[DLumi]

If we check the code for build it has a failsafe for cases when the first layer of the model is not an Input layer:

Here's the snippet from the source code

        if isinstance(self._layers[0], InputLayer):
            ...
        else:
            dtype = self._layers[0].compute_dtype
            self._layers = [
                InputLayer(batch_shape=input_shape, dtype=dtype)
            ] + self._layers

Yet the _maybe_rebuild's code ignores rebuilding entirely if input layer is missing:

    def _maybe_rebuild(self):
        self.built = False
        self._functional = None
        if isinstance(self._layers[0], InputLayer) and len(self._layers) > 1:
            input_shape = self._layers[0].batch_shape
            self.build(input_shape)

Due to that the rebuild=True argument in add() is basically ignored entirely.
The only option here is to call build() explicitly after you added all the layers.
Am I missing something? Is this the intended behavior? If so, it would be great to expand documentation on that.