Initial skeleton for IPAdapter model management.

invokeai/backend/model_management/models/base.py

@@ -1,29 +1,36 @@
+import inspect
 import json
 import os
 import sys
 import typing
-import inspect
 import warnings
 from abc import ABCMeta, abstractmethod
 from contextlib import suppress
 from enum import Enum
 from pathlib import Path
-from picklescan.scanner import scan_file_path
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Generic,
+    List,
+    Literal,
+    Optional,
+    Type,
+    TypeVar,
+    Union,
+)
 
-import torch
 import numpy as np
 import onnx
 import safetensors.torch
-from diffusers import DiffusionPipeline, ConfigMixin
-from onnx import numpy_helper
-from onnxruntime import (
-    InferenceSession,
-    SessionOptions,
-    get_available_providers,
-)
-from pydantic import BaseModel, Field
-from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
+import torch
+from diffusers import ConfigMixin, DiffusionPipeline
 from diffusers import logging as diffusers_logging
+from onnx import numpy_helper
+from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+from picklescan.scanner import scan_file_path
+from pydantic import BaseModel, Field
 from transformers import logging as transformers_logging
 
 
@@ -54,6 +61,7 @@ class ModelType(str, Enum):
     Lora = "lora"
     ControlNet = "controlnet"  # used by model_probe
     TextualInversion = "embedding"
+    IPAdapter = "ipadapter"
 
 
 class SubModelType(str, Enum):

invokeai/backend/model_management/models/ip_adapter.py

@@ -0,0 +1,53 @@
+import os
+from enum import Enum
+from typing import Any, Optional
+
+import torch
+
+from invokeai.backend.model_management.models.base import (
+    BaseModelType,
+    ModelBase,
+    ModelType,
+    SubModelType,
+    classproperty,
+)
+
+
+class IPAdapterModelFormat(Enum):
+    # The 'official' IP-Adapter model format from Tencent (i.e. https://huggingface.co/h94/IP-Adapter)
+    Tencent = "tencent"
+
+
+class IPAdapterModel(ModelBase):
+    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)
+
+        # TODO(ryand): Check correct files for model size calculation.
+        self.model_size = os.path.getsize(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}'.")
+
+        raise NotImplementedError()
+
+    @classproperty
+    def save_to_config(cls) -> bool:
+        raise NotImplementedError()
+
+    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.")
+
+        raise NotImplementedError()
+
+    def get_model(
+        self,
+        torch_dtype: Optional[torch.dtype],
+        child_type: Optional[SubModelType] = None,
+    ) -> Any:
+        if child_type is not None:
+            raise ValueError("There are no child models in an IP-Adapter model.")
+        raise NotImplementedError()