Fix issue with lowvram mode breaking model saving.

comfy/model_management.py

@@ -285,7 +285,7 @@ class LoadedModel:
         else:
             return self.model_memory()
 
-    def model_load(self, lowvram_model_memory=0):
+    def model_load(self, lowvram_model_memory=0, force_patch_weights=False):
         patch_model_to = self.device
 
         self.model.model_patches_to(self.device)
@@ -295,7 +295,7 @@ class LoadedModel:
 
         try:
             if lowvram_model_memory > 0 and load_weights:
-                self.real_model = self.model.patch_model_lowvram(device_to=patch_model_to, lowvram_model_memory=lowvram_model_memory)
+                self.real_model = self.model.patch_model_lowvram(device_to=patch_model_to, lowvram_model_memory=lowvram_model_memory, force_patch_weights=force_patch_weights)
             else:
                 self.real_model = self.model.patch_model(device_to=patch_model_to, patch_weights=load_weights)
         except Exception as e:
@@ -379,7 +379,7 @@ def free_memory(memory_required, device, keep_loaded=[]):
             if mem_free_torch > mem_free_total * 0.25:
                 soft_empty_cache()
 
-def load_models_gpu(models, memory_required=0):
+def load_models_gpu(models, memory_required=0, force_patch_weights=False):
     global vram_state
 
     inference_memory = minimum_inference_memory()
@@ -444,7 +444,7 @@ def load_models_gpu(models, memory_required=0):
         if vram_set_state == VRAMState.NO_VRAM:
             lowvram_model_memory = 64 * 1024 * 1024
 
-        cur_loaded_model = loaded_model.model_load(lowvram_model_memory)
+        cur_loaded_model = loaded_model.model_load(lowvram_model_memory, force_patch_weights=force_patch_weights)
         current_loaded_models.insert(0, loaded_model)
     return
 

comfy/model_patcher.py

@@ -272,7 +272,7 @@ class ModelPatcher:
 
         return self.model
 
-    def patch_model_lowvram(self, device_to=None, lowvram_model_memory=0):
+    def patch_model_lowvram(self, device_to=None, lowvram_model_memory=0, force_patch_weights=False):
         self.patch_model(device_to, patch_weights=False)
 
         logging.info("loading in lowvram mode {}".format(lowvram_model_memory/(1024 * 1024)))
@@ -296,8 +296,14 @@ class ModelPatcher:
 
             if lowvram_weight:
                 if weight_key in self.patches:
+                    if force_patch_weights:
+                        self.patch_weight_to_device(weight_key)
+                    else:
                         m.weight_function = LowVramPatch(weight_key, self)
                 if bias_key in self.patches:
+                    if force_patch_weights:
+                        self.patch_weight_to_device(bias_key)
+                    else:
                         m.bias_function = LowVramPatch(bias_key, self)
 
                 m.prev_comfy_cast_weights = m.comfy_cast_weights

comfy/sd.py

@@ -562,7 +562,7 @@ def save_checkpoint(output_path, model, clip=None, vae=None, clip_vision=None, m
         load_models.append(clip.load_model())
         clip_sd = clip.get_sd()
 
-    model_management.load_models_gpu(load_models)
+    model_management.load_models_gpu(load_models, force_patch_weights=True)
     clip_vision_sd = clip_vision.get_sd() if clip_vision is not None else None
     sd = model.model.state_dict_for_saving(clip_sd, vae.get_sd(), clip_vision_sd)
     for k in extra_keys:

comfy_extras/nodes_model_merging.py

@@ -262,7 +262,7 @@ class CLIPSave:
                 for x in extra_pnginfo:
                     metadata[x] = json.dumps(extra_pnginfo[x])
 
-        comfy.model_management.load_models_gpu([clip.load_model()])
+        comfy.model_management.load_models_gpu([clip.load_model()], force_patch_weights=True)
         clip_sd = clip.get_sd()
 
         for prefix in ["clip_l.", "clip_g.", ""]: