def to_dict(self) -> Dict[str, Any]:
        """
        Serializes this instance to a Python dictionary.

        Returns:
            `Dict[str, Any]`: Dictionary of all the attributes that make up this configuration instance.
        """
        output = copy.deepcopy(self.__dict__)
        if hasattr(self.__class__, "model_type"):
            output["model_type"] = self.__class__.model_type
        if "_auto_class" in output:
            del output["_auto_class"]
        if "_commit_hash" in output:
            del output["_commit_hash"]
        if "_attn_implementation_internal" in output:
            del output["_attn_implementation_internal"]

        # Transformers version when serializing the model
        output["transformers_version"] = __version__

        for key, value in output.items():
            # Deal with nested configs like CLIP
            if isinstance(value, PretrainedConfig):
                value = value.to_dict()
                del value["transformers_version"]

            output[key] = value

        if hasattr(self, "quantization_config"):
            output["quantization_config"] = (
                self.quantization_config.to_dict()
                if not isinstance(self.quantization_config, dict)
                else self.quantization_config
            )

            # pop the `_pre_quantization_dtype` as torch.dtypes are not serializable.
            _ = output.pop("_pre_quantization_dtype", None)

        self.dict_torch_dtype_to_str(output)

        return output

        Serializes this instance to a Python dictionary.

        Returns:
            `Dict[str, Any]`: Dictionary of all the attributes that make up this configuration instance.
        
smoe/models/mistral/configuration_mistral.py