Upload 2 files

app.py

@@ -399,7 +399,7 @@ class GuiSD:
             device="cpu",
         )
         self.model.load_beta_styles()
-        #self.model.device = torch.device("cpu") #
+        self.model.device = torch.device("cpu") #
 
     def load_new_model(self, model_name, vae_model, task, progress=gr.Progress(track_tqdm=True)):
 
@@ -646,15 +646,15 @@ class GuiSD:
             "high_threshold": high_threshold,
             "value_threshold": value_threshold,
             "distance_threshold": distance_threshold,
-            "lora_A": lora1 if lora1 != "None" else None,
+            "lora_A": lora1 if lora1 != "None" and lora1 != "" else None,
             "lora_scale_A": lora_scale1,
-            "lora_B": lora2 if lora2 != "None" else None,
+            "lora_B": lora2 if lora2 != "None" and lora2 != "" else None,
             "lora_scale_B": lora_scale2,
-            "lora_C": lora3 if lora3 != "None" else None,
+            "lora_C": lora3 if lora3 != "None" and lora3 != "" else None,
             "lora_scale_C": lora_scale3,
-            "lora_D": lora4 if lora4 != "None" else None,
+            "lora_D": lora4 if lora4 != "None" and lora4 != "" else None,
             "lora_scale_D": lora_scale4,
-            "lora_E": lora5 if lora5 != "None" else None,
+            "lora_E": lora5 if lora5 != "None" and lora5 != "" else None,
             "lora_scale_E": lora_scale5,
 ## BEGIN MOD
             "textual_inversion": get_embed_list(self.model.class_name) if textual_inversion else [],
@@ -704,7 +704,7 @@ class GuiSD:
         }
 
         self.model.device = torch.device("cuda:0")
-        if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * 5:
+        if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * 5 and loras_list != [""] * 5:
             self.model.pipe.transformer.to(self.model.device)
             print("transformer to cuda")
 
@@ -1707,7 +1707,7 @@ with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', elem_id="main", fill_width=True, cs
             outputs=[result_images, actual_task_info], 
             queue=True,
             show_progress="full",
-        ).success(save_gallery_images, [result_images], [result_images, result_images_files, result_images_files], queue=False, show_api=False)
+        ).success(save_gallery_images, [result_images], [result_images, result_images_files], queue=False, show_api=False)
 
         with gr.Tab("Danbooru Tags Transformer with WD Tagger", render=True):
             with gr.Column(scale=2):

modutils.py

@@ -136,7 +136,7 @@ def save_gallery_images(images, progress=gr.Progress(track_tqdm=True)):
     dt_now = datetime.now(timezone(timedelta(hours=9)))
     basename = dt_now.strftime('%Y%m%d_%H%M%S_')
     i = 1
-    if not images: return images
+    if not images: return images, gr.update(visible=False)
     output_images = []
     output_paths = []
     for image in images:
@@ -153,7 +153,7 @@ def save_gallery_images(images, progress=gr.Progress(track_tqdm=True)):
             output_paths.append(str(newpath))
             output_images.append((str(newpath), str(filename)))
     progress(1, desc="Gallery updated.")
-    return gr.update(value=output_images), gr.update(value=output_paths), gr.update(visible=True)
+    return gr.update(value=output_images), gr.update(value=output_paths, visible=True)
 
 
 def download_private_repo(repo_id, dir_path, is_replace):