Method to_json_string

src/diffusers/configuration_utils.py:619–662

Serializes the configuration instance to a JSON string. Returns: `str`: String containing all the attributes that make up the configuration instance in JSON format.

(self)

        return self._internal_dict

    def to_json_string(self) -> str:
        """
        Serializes the configuration instance to a JSON string.

        Returns:
            `str`:
                String containing all the attributes that make up the configuration instance in JSON format.
        """
        config_dict = self._internal_dict if hasattr(self, "_internal_dict") else {}
        config_dict["_class_name"] = self.__class__.__name__
        config_dict["_diffusers_version"] = __version__

        def to_json_saveable(value):
            if isinstance(value, np.ndarray):
                value = value.tolist()
            elif isinstance(value, Path):
                value = value.as_posix()
            elif hasattr(value, "to_dict") and callable(value.to_dict):
                value = value.to_dict()
            elif isinstance(value, list):
                value = [to_json_saveable(v) for v in value]
            return value

        if "quantization_config" in config_dict:
            config_dict["quantization_config"] = (
                config_dict.quantization_config.to_dict()
                if not isinstance(config_dict.quantization_config, dict)
                else config_dict.quantization_config
            )

        config_dict = {k: to_json_saveable(v) for k, v in config_dict.items()}
        # Don't save "_ignore_files" or "_use_default_values"
        config_dict.pop("_ignore_files", None)
        config_dict.pop("_use_default_values", None)
        # pop the `_pre_quantization_dtype` as torch.dtypes are not serializable.
        _ = config_dict.pop("_pre_quantization_dtype", None)

        if getattr(self, "_auto_class", None) is not None:
            module = self.__class__.__module__.split(".")[-1]
            auto_map = config_dict.get("auto_map", {})
            auto_map[self._auto_class] = f"{module}.{self.__class__.__name__}"
            config_dict["auto_map"] = auto_map

        return json.dumps(config_dict, indent=2, sort_keys=True) + "\n"

    def to_json_file(self, json_file_path: str | os.PathLike):
        """