Fix OOMs happening in some cases.

A cloned model patcher sometimes reported a model was loaded on a device
when it wasn't.

comfy/model_base.py

@@ -74,6 +74,7 @@ class BaseModel(torch.nn.Module):
         self.latent_format = model_config.latent_format
         self.model_config = model_config
         self.manual_cast_dtype = model_config.manual_cast_dtype
+        self.device = device
 
         if not unet_config.get("disable_unet_model_creation", False):
             if self.manual_cast_dtype is not None:

comfy/model_management.py

@@ -274,7 +274,7 @@ class LoadedModel:
         return self.model.model_size()
 
     def model_memory_required(self, device):
-        if device == self.model.current_device:
+        if device == self.model.current_loaded_device():
             return 0
         else:
             return self.model_memory()

comfy/model_patcher.py

@@ -64,9 +64,15 @@ def set_model_options_pre_cfg_function(model_options, pre_cfg_function, disable_
     return model_options
 
 class ModelPatcher:
-    def __init__(self, model, load_device, offload_device, size=0, current_device=None, weight_inplace_update=False):
+    def __init__(self, model, load_device, offload_device, size=0, weight_inplace_update=False):
         self.size = size
         self.model = model
+        if not hasattr(self.model, 'device'):
+            logging.info("Model doesn't have a device attribute.")
+            self.model.device = offload_device
+        elif self.model.device is None:
+            self.model.device = offload_device
+
         self.patches = {}
         self.backup = {}
         self.object_patches = {}
@@ -75,11 +81,6 @@ class ModelPatcher:
         self.model_size()
         self.load_device = load_device
         self.offload_device = offload_device
-        if current_device is None:
-            self.current_device = self.offload_device
-        else:
-            self.current_device = current_device
-
         self.weight_inplace_update = weight_inplace_update
         self.model_lowvram = False
         self.lowvram_patch_counter = 0
@@ -92,7 +93,7 @@ class ModelPatcher:
         return self.size
 
     def clone(self):
-        n = ModelPatcher(self.model, self.load_device, self.offload_device, self.size, self.current_device, weight_inplace_update=self.weight_inplace_update)
+        n = ModelPatcher(self.model, self.load_device, self.offload_device, self.size, weight_inplace_update=self.weight_inplace_update)
         n.patches = {}
         for k in self.patches:
             n.patches[k] = self.patches[k][:]
@@ -302,7 +303,7 @@ class ModelPatcher:
 
             if device_to is not None:
                 self.model.to(device_to)
-                self.current_device = device_to
+                self.model.device = device_to
 
         return self.model
 
@@ -355,6 +356,7 @@ class ModelPatcher:
 
         self.model_lowvram = True
         self.lowvram_patch_counter = patch_counter
+        self.model.device = device_to
         return self.model
 
     def calculate_weight(self, patches, weight, key):
@@ -551,10 +553,13 @@ class ModelPatcher:
 
             if device_to is not None:
                 self.model.to(device_to)
-                self.current_device = device_to
+                self.model.device = device_to
 
         keys = list(self.object_patches_backup.keys())
         for k in keys:
             comfy.utils.set_attr(self.model, k, self.object_patches_backup[k])
 
         self.object_patches_backup.clear()
+
+    def current_loaded_device(self):
+        return self.model.device

comfy/sd.py

@@ -564,7 +564,7 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o
         logging.debug("left over keys: {}".format(left_over))
 
     if output_model:
-        model_patcher = comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=model_management.unet_offload_device(), current_device=inital_load_device)
+        model_patcher = comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=model_management.unet_offload_device())
         if inital_load_device != torch.device("cpu"):
             logging.info("loaded straight to GPU")
             model_management.load_model_gpu(model_patcher)