def initialize_dummy_weights(model, model_config, ...):
    meta_device_params: set[int] = set()
    for module in model.modules():
        qm = getattr(module, "quant_method", None)
        if qm is not None and getattr(qm, "uses_meta_device", False):
            for param in module.parameters(recurse=False):
                meta_device_params.add(id(param))

    for param in model.state_dict().values():
        if id(param) in meta_device_params \
                and param.device == torch.device("meta"):
            continue
        initialize_single_dummy_weight(param, low, high, seed)

def initialize_dummy_weights(
    model: torch.nn.Module,
    model_config: ModelConfig,
    low: float = -1e-3,
    high: float = 1e-3,
    seed: int = 1234,
) -> None:
    def uses_meta_device(module: torch.nn.Module) -> bool:
        quant_method = getattr(module, "quant_method", None)
        return getattr(quant_method, "uses_meta_device", False)

    has_online_quant = any(uses_meta_device(m) for m in model.modules())

    for param in model.state_dict().values():
        if has_online_quant and param.device == torch.device("meta"):
            # For online quantization, weights are created on meta device and
            # dummy weight init will happen in `process_weights_after_loading`.
            continue

        initialize_single_dummy_weight(param, low, high, seed)