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chore: import upstream snapshot with attribution
2026-07-13 13:22:06 +08:00

35 lines
1.4 KiB
Python

# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
"""Class for IP Adapter model loading in InvokeAI."""
from pathlib import Path
from typing import Optional
import torch
from invokeai.backend.ip_adapter.ip_adapter import build_ip_adapter
from invokeai.backend.model_manager.configs.factory import AnyModelConfig
from invokeai.backend.model_manager.load import ModelLoader, ModelLoaderRegistry
from invokeai.backend.model_manager.taxonomy import AnyModel, BaseModelType, ModelFormat, ModelType, SubModelType
from invokeai.backend.raw_model import RawModel
@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.Checkpoint)
class IPAdapterInvokeAILoader(ModelLoader):
"""Class to load IP Adapter diffusers models."""
def _load_model(
self,
config: AnyModelConfig,
submodel_type: Optional[SubModelType] = None,
) -> AnyModel:
if submodel_type is not None:
raise ValueError("There are no submodels in an IP-Adapter model.")
model_path = Path(config.path)
model: RawModel = build_ip_adapter(
ip_adapter_ckpt_path=model_path,
device=torch.device("cpu"),
dtype=self._torch_dtype,
)
return model