import os import typing from enum import Enum from typing import Literal, Optional import torch from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus, build_ip_adapter from invokeai.backend.model_management.models.base import ( BaseModelType, InvalidModelException, ModelBase, ModelConfigBase, ModelType, SubModelType, calc_model_size_by_fs, classproperty, ) class IPAdapterModelFormat(str, Enum): # The custom IP-Adapter model format defined by InvokeAI. InvokeAI = "invokeai" class IPAdapterModel(ModelBase): class InvokeAIConfig(ModelConfigBase): model_format: Literal[IPAdapterModelFormat.InvokeAI] def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType): assert model_type == ModelType.IPAdapter super().__init__(model_path, base_model, model_type) self.model_size = calc_model_size_by_fs(self.model_path) @classmethod def detect_format(cls, path: str) -> str: if not os.path.exists(path): raise ModuleNotFoundError(f"No IP-Adapter model at path '{path}'.") if os.path.isdir(path): model_file = os.path.join(path, "ip_adapter.bin") image_encoder_config_file = os.path.join(path, "image_encoder.txt") if os.path.exists(model_file) and os.path.exists(image_encoder_config_file): return IPAdapterModelFormat.InvokeAI raise InvalidModelException(f"Unexpected IP-Adapter model format: {path}") @classproperty def save_to_config(cls) -> bool: return True def get_size(self, child_type: Optional[SubModelType] = None) -> int: if child_type is not None: raise ValueError("There are no child models in an IP-Adapter model.") return self.model_size def get_model( self, torch_dtype: torch.dtype, child_type: Optional[SubModelType] = None, ) -> typing.Union[IPAdapter, IPAdapterPlus]: if child_type is not None: raise ValueError("There are no child models in an IP-Adapter model.") model = build_ip_adapter( ip_adapter_ckpt_path=os.path.join(self.model_path, "ip_adapter.bin"), device=torch.device("cpu"), dtype=torch_dtype, ) self.model_size = model.calc_size() return model @classmethod def convert_if_required( cls, model_path: str, output_path: str, config: ModelConfigBase, base_model: BaseModelType, ) -> str: format = cls.detect_format(model_path) if format == IPAdapterModelFormat.InvokeAI: return model_path else: raise ValueError(f"Unsupported format: '{format}'.") def get_ip_adapter_image_encoder_model_id(model_path: str): """Read the ID of the image encoder associated with the IP-Adapter at `model_path`.""" image_encoder_config_file = os.path.join(model_path, "image_encoder.txt") with open(image_encoder_config_file, "r") as f: image_encoder_model = f.readline().strip() return image_encoder_model