Method from_config

src/diffusers/configuration_utils.py:223–312

r""" Instantiate a Python class from a config dictionary. Parameters: config (`dict[str, Any]`): A config dictionary from which the Python class is instantiated. Make sure to only load configuration files of compatible classes.

(
        cls, config: FrozenDict | dict[str, Any] = None, return_unused_kwargs=False, **kwargs
    )

    @classmethod
    def from_config(
        cls, config: FrozenDict | dict[str, Any] = None, return_unused_kwargs=False, **kwargs
    ) -> Self | tuple[Self, dict[str, Any]]:
        r"""
        Instantiate a Python class from a config dictionary.

        Parameters:
            config (`dict[str, Any]`):
                A config dictionary from which the Python class is instantiated. Make sure to only load configuration
                files of compatible classes.
            return_unused_kwargs (`bool`, *optional*, defaults to `False`):
                Whether kwargs that are not consumed by the Python class should be returned or not.
            kwargs (remaining dictionary of keyword arguments, *optional*):
                Can be used to update the configuration object (after it is loaded) and initiate the Python class.
                `**kwargs` are passed directly to the underlying scheduler/model's `__init__` method and eventually
                overwrite the same named arguments in `config`.

        Returns:
            [`ModelMixin`] or [`SchedulerMixin`]:
                A model or scheduler object instantiated from a config dictionary.

        Examples:

        ```python
        >>> from diffusers import DDPMScheduler, DDIMScheduler, PNDMScheduler

        >>> # Download scheduler from huggingface.co and cache.
        >>> scheduler = DDPMScheduler.from_pretrained("google/ddpm-cifar10-32")

        >>> # Instantiate DDIM scheduler class with same config as DDPM
        >>> scheduler = DDIMScheduler.from_config(scheduler.config)

        >>> # Instantiate PNDM scheduler class with same config as DDPM
        >>> scheduler = PNDMScheduler.from_config(scheduler.config)
        ```
        """
        # <===== TO BE REMOVED WITH DEPRECATION
        # TODO(Patrick) - make sure to remove the following lines when config=="model_path" is deprecated
        if "pretrained_model_name_or_path" in kwargs:
            config = kwargs.pop("pretrained_model_name_or_path")

        if config is None:
            raise ValueError("Please make sure to provide a config as the first positional argument.")
        # ======>

        if not isinstance(config, dict):
            deprecation_message = "It is deprecated to pass a pretrained model name or path to `from_config`."
            if "Scheduler" in cls.__name__:
                deprecation_message += (
                    f"If you were trying to load a scheduler, please use {cls}.from_pretrained(...) instead."
                    " Otherwise, please make sure to pass a configuration dictionary instead. This functionality will"
                    " be removed in v1.0.0."
                )
            elif "Model" in cls.__name__:
                deprecation_message += (
                    f"If you were trying to load a model, please use {cls}.load_config(...) followed by"
                    f" {cls}.from_config(...) instead. Otherwise, please make sure to pass a configuration dictionary"
                    " instead. This functionality will be removed in v1.0.0."