Merge branch 'main' into lstein/default-model-install

invokeai/backend/install/migrate_to_3.py

@@ -593,9 +593,12 @@ script, which will perform a full upgrade in place."""
     config = InvokeAIAppConfig.get_config()
     config.parse_args(['--root',str(dest_root)])
 
-    # TODO: revisit
-    # assert (dest_root / 'models').is_dir(), f"{dest_root} does not contain a 'models' subdirectory"
-    # assert (dest_root / 'invokeai.yaml').exists(), f"{dest_root} does not contain an InvokeAI init file."
+    # TODO: revisit - don't rely on invokeai.yaml to exist yet!
+    dest_is_setup = (dest_root / 'models/core').exists() and (dest_root / 'databases').exists()
+    if not dest_is_setup:
+        import invokeai.frontend.install.invokeai_configure
+        from invokeai.backend.install.invokeai_configure import initialize_rootdir
+        initialize_rootdir(dest_root, True)
 
     do_migrate(src_root,dest_root)
 

invokeai/backend/model_management/models/controlnet.py

@@ -1,8 +1,7 @@
 import os
 import torch
 from enum import Enum
-from pathlib import Path
-from typing import Optional, Union, Literal
+from typing import Optional
 from .base import (
     ModelBase,
     ModelConfigBase,
@@ -14,6 +13,7 @@ from .base import (
     calc_model_size_by_data,
     classproperty,
     InvalidModelException,
+    ModelNotFoundException,
 )
 
 class ControlNetModelFormat(str, Enum):
@@ -60,10 +60,20 @@ class ControlNetModel(ModelBase):
         if child_type is not None:
             raise Exception("There is no child models in controlnet model")
 
-        model = self.model_class.from_pretrained(
-            self.model_path,
-            torch_dtype=torch_dtype,
-        )
+        model = None
+        for variant in ['fp16',None]:
+            try:
+                model = self.model_class.from_pretrained(
+                    self.model_path,
+                    torch_dtype=torch_dtype,
+                    variant=variant,
+                )
+                break
+            except:
+                pass
+        if not model:
+            raise ModelNotFoundException()
+        
         # calc more accurate size
         self.model_size = calc_model_size_by_data(model)
         return model