diffusers/pr_11739/en/api/configuration.md

Configuration

Schedulers from SchedulerMixin and models from ModelMixin inherit from ConfigMixin which stores all the parameters that are passed to their respective __init__ methods in a JSON-configuration file.

To use private or gated models, log-in with hf auth login.

ConfigMixin[[diffusers.ConfigMixin]]

diffusers.ConfigMixin[[diffusers.ConfigMixin]]

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Base class for all configuration classes. All configuration parameters are stored under self.config. Also provides the from_config() and save_config() methods for loading, downloading, and saving classes that inherit from ConfigMixin.

Class attributes:

• config_name (str) -- A filename under which the config should stored when calling save_config() (should be overridden by parent class).
• ignore_for_config (List[str]) -- A list of attributes that should not be saved in the config (should be overridden by subclass).
• has_compatibles (bool) -- Whether the class has compatible classes (should be overridden by subclass).
• _deprecated_kwargs (List[str]) -- Keyword arguments that are deprecated. Note that the init function should only have a kwargs argument if at least one argument is deprecated (should be overridden by subclass).

load_configdiffusers.ConfigMixin.load_confighttps://github.com/huggingface/diffusers/blob/vr_11739/src/diffusers/configuration_utils.py#L291[{"name": "pretrained_model_name_or_path", "val": ": typing.Union[str, os.PathLike]"}, {"name": "return_unused_kwargs", "val": " = False"}, {"name": "return_commit_hash", "val": " = False"}, {"name": "**kwargs", "val": ""}]- pretrained_model_name_or_path (str or os.PathLike, optional) -- Can be either:

• A string, the model id (for example google/ddpm-celebahq-256) of a pretrained model hosted on the Hub.

• A path to a directory (for example ./my_model_directory) containing model weights saved with save_config().

• cache_dir (Union[str, os.PathLike], optional) -- Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not used.

• force_download (bool, optional, defaults to False) -- Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.

• proxies (Dict[str, str], optional) -- A dictionary of proxy servers to use by protocol or endpoint, for example, {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request.

• output_loading_info(bool, optional, defaults to False) -- Whether or not to also return a dictionary containing missing keys, unexpected keys and error messages.

• local_files_only (bool, optional, defaults to False) -- Whether to only load local model weights and configuration files or not. If set to True, the model won't be downloaded from the Hub.

• token (str or bool, optional) -- The token to use as HTTP bearer authorization for remote files. If True, the token generated from diffusers-cli login (stored in ~/.huggingface) is used.

• revision (str, optional, defaults to "main") -- The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier allowed by Git.

• subfolder (str, optional, defaults to "") -- The subfolder location of a model file within a larger model repository on the Hub or locally.

• return_unused_kwargs (bool, optional, defaults to `False) -- Whether unused keyword arguments of the config are returned.

• return_commit_hash (bool, optional, defaults to False) -- Whether the commit_hash of the loaded configuration are returned.0dict`A dictionary of all the parameters stored in a JSON configuration file.

Load a model or scheduler configuration.

Parameters:

pretrained_model_name_or_path (str or os.PathLike, optional) : Can be either: - A string, the model id (for example google/ddpm-celebahq-256) of a pretrained model hosted on the Hub. - A path to a directory (for example ./my_model_directory) containing model weights saved with save_config().

cache_dir (Union[str, os.PathLike], optional) : Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not used.

force_download (bool, optional, defaults to False) : Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.

proxies (Dict[str, str], optional) : A dictionary of proxy servers to use by protocol or endpoint, for example, {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}. The proxies are used on each request.

output_loading_info(bool, optional, defaults to False) : Whether or not to also return a dictionary containing missing keys, unexpected keys and error messages.

local_files_only (bool, optional, defaults to False) : Whether to only load local model weights and configuration files or not. If set to True, the model won't be downloaded from the Hub.

token (str or bool, optional) : The token to use as HTTP bearer authorization for remote files. If True, the token generated from diffusers-cli login (stored in ~/.huggingface) is used.

revision (str, optional, defaults to "main") : The specific model version to use. It can be a branch name, a tag name, a commit id, or any identifier allowed by Git.

subfolder (str, optional, defaults to "") : The subfolder location of a model file within a larger model repository on the Hub or locally.

return_unused_kwargs (bool, optional, defaults to `False) : Whether unused keyword arguments of the config are returned.

return_commit_hash (bool, optional, defaults to False) : Whether the commit_hash` of the loaded configuration are returned.

Returns:

dict

A dictionary of all the parameters stored in a JSON configuration file.

from_config[[diffusers.ConfigMixin.from_config]]

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Instantiate a Python class from a config dictionary.

Examples:

>>> 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)

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](/docs/diffusers/pr_11739/en/api/models/overview#diffusers.ModelMixin) or [SchedulerMixin](/docs/diffusers/pr_11739/en/api/schedulers/overview#diffusers.SchedulerMixin)

A model or scheduler object instantiated from a config dictionary.

save_config[[diffusers.ConfigMixin.save_config]]

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Save a configuration object to the directory specified in save_directory so that it can be reloaded using the from_config() class method.

Parameters:

save_directory (str or os.PathLike) : Directory where the configuration JSON file is saved (will be created if it does not exist).

push_to_hub (bool, optional, defaults to False) : Whether or not to push your model to the Hugging Face Hub after saving it. You can specify the repository you want to push to with repo_id (will default to the name of save_directory in your namespace).

kwargs (Dict[str, Any], optional) : Additional keyword arguments passed along to the push_to_hub() method.

to_json_file[[diffusers.ConfigMixin.to_json_file]]

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Save the configuration instance's parameters to a JSON file.

Parameters:

json_file_path (str or os.PathLike) : Path to the JSON file to save a configuration instance's parameters.

to_json_string[[diffusers.ConfigMixin.to_json_string]]

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Serializes the configuration instance to a JSON string.

Returns:

str

String containing all the attributes that make up the configuration instance in JSON format.