fix:lora

modules/scripts.py

@@ -181,7 +181,6 @@ def list_scripts(scriptdirname, extension):
 
     scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)]
 
-    print("111111111 scripts_list", scripts_list)
     return scripts_list
 
 

predict.py

@@ -42,7 +42,7 @@ import modules.textual_inversion.textual_inversion
 import modules.progress
 
 import modules.ui
-from modules import modelloader
+from modules import modelloader, extensions
 from modules.shared import cmd_opts, opts
 import modules.hypernetworks.hypernetwork
 
@@ -50,6 +50,7 @@ from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusion
 
 
 def initialize():
+    extensions.list_extensions()
     modelloader.cleanup_models()
     modules.sd_models.setup_model()
     codeformer.setup_model(cmd_opts.codeformer_models_path)
@@ -94,7 +95,7 @@ class Predictor(BasePredictor):
         self,
         prompt: str = Input(description="prompt en", default="lora:koreanDollLikeness_v15:0.66, best quality, ultra high res, (photorealistic:1.4), 1girl, beige sweater, black choker, smile, laughing, bare shoulders, solo focus, ((full body), (brown hair:1), looking at viewer"),
         negative_prompt: str = Input(description="negative prompt", default="paintings, sketches, (worst quality:2), (low quality:2), (normal quality:2), lowres, normal quality, ((monochrome)), ((grayscale)), skin spots, acnes, skin blemishes, age spot, glans, (ugly:1.331), (duplicate:1.331), (morbid:1.21), (mutilated:1.21), (tranny:1.331), mutated hands, (poorly drawn hands:1.331), blurry, 3hands,4fingers,3arms, bad anatomy, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts,poorly drawn face,mutation,deformed"),
-        sampler_name: str = Input(description="sampler name", default="DPM++ SDE Karras", choices=["DPM++ SDE Karras", "DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "LMS Karras", "DPM adaptive", "DPM fast", "DPM++ SDE", "DPM++ 2M", "DPM++ 2S a", "DPM2 a", "DPM2", "Heun", "LMS", "Euler", "Euler a"]),
+        sampler_name: str = Input(description="sampler name", default="DPM++ 2M Karras", choices=["DPM++ SDE Karras", "DPM++ 2M Karras", "DPM++ 2S a Karras", "DPM2 a Karras", "DPM2 Karras", "LMS Karras", "DPM adaptive", "DPM fast", "DPM++ SDE", "DPM++ 2M", "DPM++ 2S a", "DPM2 a", "DPM2", "Heun", "LMS", "Euler", "Euler a"]),
         steps: int = Input(description="steps", default=20),
         cfg_scale: int = Input(description="cfg scale", default=8),
         width: int = Input(description="width", default=512),
@@ -102,7 +103,6 @@ class Predictor(BasePredictor):
         seed: int = Input(description="seed", default=-1),
     ) -> Path:
         """Run a single prediction on the model"""
-        modules.script_callbacks.before_ui_callback()
         args = {
             "do_not_save_samples": True,
             "do_not_save_grid": True,