Lower lora ram usage when in normal vram mode.

comfy/model_management.py

@@ -233,10 +233,9 @@ def unload_model():
             accelerate.hooks.remove_hook_from_submodules(current_loaded_model.model)
             model_accelerated = False
 
-
+        current_loaded_model.unpatch_model()
         current_loaded_model.model.to(current_loaded_model.offload_device)
         current_loaded_model.model_patches_to(current_loaded_model.offload_device)
-        current_loaded_model.unpatch_model()
         current_loaded_model = None
         if vram_state != VRAMState.HIGH_VRAM:
             soft_empty_cache()
@@ -282,14 +281,6 @@ def load_model_gpu(model):
     elif vram_set_state == VRAMState.NORMAL_VRAM or vram_set_state == VRAMState.HIGH_VRAM or vram_set_state == VRAMState.SHARED:
         model_accelerated = False
         real_model.to(torch_dev)
-    else:
-        if vram_set_state == VRAMState.NO_VRAM:
-            device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"})
-        elif vram_set_state == VRAMState.LOW_VRAM:
-            device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "{}MiB".format(lowvram_model_memory // (1024 * 1024)), "cpu": "16GiB"})
-
-        accelerate.dispatch_model(real_model, device_map=device_map, main_device=torch_dev)
-        model_accelerated = True
 
     try:
         real_model = model.patch_model()
@@ -298,6 +289,15 @@ def load_model_gpu(model):
         unload_model()
         raise e
 
+    if vram_set_state == VRAMState.NO_VRAM:
+        device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "256MiB", "cpu": "16GiB"})
+        accelerate.dispatch_model(real_model, device_map=device_map, main_device=torch_dev)
+        model_accelerated = True
+    elif vram_set_state == VRAMState.LOW_VRAM:
+        device_map = accelerate.infer_auto_device_map(real_model, max_memory={0: "{}MiB".format(lowvram_model_memory // (1024 * 1024)), "cpu": "16GiB"})
+        accelerate.dispatch_model(real_model, device_map=device_map, main_device=torch_dev)
+        model_accelerated = True
+
     return current_loaded_model
 
 def load_controlnet_gpu(control_models):

comfy/sd.py

@@ -428,11 +428,17 @@ class ModelPatcher:
         return weight
 
     def unpatch_model(self):
-        model_sd = self.model_state_dict()
         keys = list(self.backup.keys())
+        def set_attr(obj, attr, value):
+            attrs = attr.split(".")
+            for name in attrs[:-1]:
+                obj = getattr(obj, name)
+            prev = getattr(obj, attrs[-1])
+            setattr(obj, attrs[-1], torch.nn.Parameter(value))
+            del prev
+
         for k in keys:
-            model_sd[k][:] = self.backup[k]
-            del self.backup[k]
+            set_attr(self.model, k, self.backup[k])
 
         self.backup = {}