def merge_quantization_configs(
        cls,
        quantization_config: Union[dict, QuantizationConfigMixin],
        quantization_config_from_args: Optional[QuantizationConfigMixin],
    ):
        """
        handles situations where both quantization_config from args and quantization_config from model config are
        present.
        """
        if quantization_config_from_args is not None:
            warning_msg = (
                "You passed `quantization_config` or equivalent parameters to `from_pretrained` but the model you're loading"
                " already has a `quantization_config` attribute. The `quantization_config` from the model will be used."
            )
        else:
            warning_msg = ""

        if isinstance(quantization_config, dict):
            quantization_config = cls.from_dict(quantization_config)

        if warning_msg != "":
            warnings.warn(warning_msg)

        return quantization_config

        handles situations where both quantization_config from args and quantization_config from model config are
        present.
        
src/diffusers/quantizers/auto.py