Use CLIPVisionModel under model management for IP-Adapter.

invokeai/backend/model_management/models/clip_vision.py

@@ -60,7 +60,7 @@ class CLIPVisionModel(ModelBase):
         if child_type is not None:
             raise ValueError("There are no child models in a CLIP Vision model.")
 
-        model = CLIPVisionModelWithProjection.from_pretrained(self._image_encoder_path, torch_dtype=torch_dtype)
+        model = CLIPVisionModelWithProjection.from_pretrained(self.model_path, torch_dtype=torch_dtype)
 
         # Calculate a more accurate model size.
         self.model_size = calc_model_size_by_data(model)

invokeai/backend/model_management/models/ip_adapter.py

@@ -55,10 +55,6 @@ class IPAdapterModel(ModelBase):
         # TODO(ryand): Update self.model_size when the model is loaded from disk.
         return self.model_size
 
-    def _get_text_encoder_path(self) -> str:
-        # TODO(ryand): Move the CLIP image encoder to its own model directory.
-        return os.path.join(os.path.dirname(self.model_path), "image_encoder")
-
     def get_model(
         self,
         torch_dtype: Optional[torch.dtype],
@@ -72,13 +68,9 @@ class IPAdapterModel(ModelBase):
         # TODO(ryand): Checking for "plus" in the file name is fragile. It should be possible to infer whether this is a
         # "plus" variant by loading the state_dict.
         if "plus" in str(self.model_path):
-            return IPAdapterPlus(
-                image_encoder_path=self._get_text_encoder_path(), ip_adapter_ckpt_path=self.model_path, device="cpu"
-            )
+            return IPAdapterPlus(ip_adapter_ckpt_path=self.model_path, device="cpu")
         else:
-            return IPAdapter(
-                image_encoder_path=self._get_text_encoder_path(), ip_adapter_ckpt_path=self.model_path, device="cpu"
-            )
+            return IPAdapter(ip_adapter_ckpt_path=self.model_path, device="cpu")
 
     @classmethod
     def convert_if_required(