(name: str = 'custom', type_name: str = 'CUSTOM')

(name: str = 'enum_field', options: Iterable = [])

(required: Iterable = [], optional: Iterable = [])

(name: str = 'int_field', default: int = 50, minimum: int = 0, maximum: int = 100, step: int = 1)

(model_type)

(name: str = 'bool_field', default: bool = False)

(self, **kwagrs)

(self, shape: Tuple[int])

(name: str = 'image')

(images: Iterable[Image.Image])

(self, coeffs: torch.Tensor, basis: torch.Tensor)

(tensor: torch.Tensor)

()

(cls)

(landmark: np.ndarray)

(image: Image.Image, landmark: np.ndarray, mask_scale: float = 1.0)

(self)

(name: str = 'str_field', default: str = '', multiline: bool = False)

(name: str = 'float_field', default: float = 0.5, minimum: float = 0.0, maximum: float = 1.0, step: float = 0.

(self, config_dict: Dict[str, Any])

(model, clip, lora, strength_model, strength_clip)

(self, hyper_lora: HyperLoRA, image: Image.Image, face_attr: FaceAttrResp, crop, crop_scale_LRTB, safe_crop)

(self, hyper_lora: HyperLoRA, image: Image.Image, face_attr: FaceAttrResp, grayscale, remove_background)

(self, x)

(self, indent: int = 0)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(cls)

(self, dim, dim_head=64, heads=8, ff_mult=4, n_conds=1)

(self, dim=1024, depth=8, dim_head=64, heads=8, num_queries=16, embedding_dim=768, output_dim=1024, ff_mult=4,

(self, dim: int, in_features: int, out_features: int, lora_rank: int = 4, has_base_lora: bool = False)

(self, dim: int, hidden_size: int, cross_attention_dim: int, lora_rank: int = 4, has_base_lora: bool = False)

(**arg_types: Dict[str, BatchType])

(self, config: HyperLoRAConfig, model, dtype)

(self, hyper_lora: HyperLoRA, images: torch.Tensor, face_attr: list[FaceAttrResp], grayscale, remove_backgroun

(self, hyper_lora: HyperLoRA, images: torch.Tensor, face_attr: list[FaceAttrResp], crop, crop_scale_LRTB, safe

(self, hyper_lora: HyperLoRA, id_cond)

(self, hyper_lora: HyperLoRA, base_cond)

(self, model: ModelPatcher, lora, weight)

(self, filename_prefix, lora)

(self, hyper_lora: HyperLoRA, images: torch.Tensor)

(self, image_processor, image_encoder, encoder_types, face_analyzer, model, dtype)

(self, hyper_lora, images, grayscale, remove_background)

(self, x, latents, y=None)

(self, x, y=None)

(self, tokens: torch.Tensor, mode='id')

(self, tokens: torch.Tensor, mode='id')

(self, x: torch.Tensor)

(image: Image.Image)

(url: str)

(self)

(self)

(name: str = 'mask')

(image: Image.Image, size: int, mode: ResizeMode = ResizeMode.LONG_EDGE)

(*args: List[Any], **kwargs: Dict[str, Any])

(func: Callable)