Fix some performance issues with weight loading and unloading.

Lower peak memory usage when changing model.

Fix case where model weights would be unloaded and reloaded.

comfy/model_management.py

@@ -274,6 +274,7 @@ class LoadedModel:
         self.model = model
         self.device = model.load_device
         self.weights_loaded = False
+        self.real_model = None
 
     def model_memory(self):
         return self.model.model_size()
@@ -312,6 +313,7 @@ class LoadedModel:
         self.model.unpatch_model(self.model.offload_device, unpatch_weights=unpatch_weights)
         self.model.model_patches_to(self.model.offload_device)
         self.weights_loaded = self.weights_loaded and not unpatch_weights
+        self.real_model = None
 
     def __eq__(self, other):
         return self.model is other.model
@@ -326,7 +328,7 @@ def unload_model_clones(model, unload_weights_only=True, force_unload=True):
             to_unload = [i] + to_unload
 
     if len(to_unload) == 0:
-        return None
+        return True
 
     same_weights = 0
     for i in to_unload:
@@ -408,8 +410,8 @@ def load_models_gpu(models, memory_required=0):
 
     total_memory_required = {}
     for loaded_model in models_to_load:
-        unload_model_clones(loaded_model.model, unload_weights_only=True, force_unload=False) #unload clones where the weights are different
-        total_memory_required[loaded_model.device] = total_memory_required.get(loaded_model.device, 0) + loaded_model.model_memory_required(loaded_model.device)
+        if unload_model_clones(loaded_model.model, unload_weights_only=True, force_unload=False) == True:#unload clones where the weights are different
+            total_memory_required[loaded_model.device] = total_memory_required.get(loaded_model.device, 0) + loaded_model.model_memory_required(loaded_model.device)
 
     for device in total_memory_required:
         if device != torch.device("cpu"):
@@ -448,11 +450,15 @@ def load_models_gpu(models, memory_required=0):
 def load_model_gpu(model):
     return load_models_gpu([model])
 
-def cleanup_models():
+def cleanup_models(keep_clone_weights_loaded=False):
     to_delete = []
     for i in range(len(current_loaded_models)):
         if sys.getrefcount(current_loaded_models[i].model) <= 2:
-            to_delete = [i] + to_delete
+            if not keep_clone_weights_loaded:
+                to_delete = [i] + to_delete
+            #TODO: find a less fragile way to do this.
+            elif sys.getrefcount(current_loaded_models[i].real_model) <= 3: #references from .real_model + the .model
+                to_delete = [i] + to_delete
 
     for i in to_delete:
         x = current_loaded_models.pop(i)

execution.py

@@ -368,6 +368,7 @@ class PromptExecutor:
                     d = self.outputs_ui.pop(x)
                     del d
 
+            comfy.model_management.cleanup_models(keep_clone_weights_loaded=True)
             self.add_message("execution_cached",
                           { "nodes": list(current_outputs) , "prompt_id": prompt_id},
                           broadcast=False)