LoraLoader node now caches the lora file between executions.

comfy/sd.py

@@ -89,8 +89,7 @@ LORA_UNET_MAP_RESNET = {
     "skip_connection": "resnets_{}_conv_shortcut"
 }
 
-def load_lora(path, to_load):
-    lora = utils.load_torch_file(path, safe_load=True)
+def load_lora(lora, to_load):
     patch_dict = {}
     loaded_keys = set()
     for x in to_load:
@@ -501,10 +500,10 @@ class ModelPatcher:
 
         self.backup = {}
 
-def load_lora_for_models(model, clip, lora_path, strength_model, strength_clip):
+def load_lora_for_models(model, clip, lora, strength_model, strength_clip):
     key_map = model_lora_keys(model.model)
     key_map = model_lora_keys(clip.cond_stage_model, key_map)
-    loaded = load_lora(lora_path, key_map)
+    loaded = load_lora(lora, key_map)
     new_modelpatcher = model.clone()
     k = new_modelpatcher.add_patches(loaded, strength_model)
     new_clip = clip.clone()

nodes.py

@@ -434,6 +434,9 @@ class CLIPSetLastLayer:
         return (clip,)
 
 class LoraLoader:
+    def __init__(self):
+        self.loaded_lora = None
+
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { "model": ("MODEL",),
@@ -452,7 +455,18 @@ class LoraLoader:
             return (model, clip)
 
         lora_path = folder_paths.get_full_path("loras", lora_name)
-        model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora_path, strength_model, strength_clip)
+        lora = None
+        if self.loaded_lora is not None:
+            if self.loaded_lora[0] == lora_path:
+                lora = self.loaded_lora[1]
+            else:
+                del self.loaded_lora
+
+        if lora is None:
+            lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
+            self.loaded_lora = (lora_path, lora)
+
+        model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip)
         return (model_lora, clip_lora)
 
 class VAELoader: