Upload 2 files

dc.py

@@ -191,7 +191,7 @@ class GuiSD:
 
                 if self.model.base_model_id != model_name:
                     load_now_time = datetime.now()
-                    elapsed_time = (load_now_time - self.last_load).total_seconds()
+                    elapsed_time = max((load_now_time - self.last_load).total_seconds(), 0)
 
                     if elapsed_time <= 8:
                         print("Waiting for the previous model's time ops...")
@@ -220,7 +220,7 @@ class GuiSD:
         yield f"Model loaded: {model_name}"
 
     #@spaces.GPU
-    #@torch.inference_mode()
+    @torch.inference_mode()
     def generate_pipeline(
         self,
         prompt,
@@ -549,7 +549,6 @@ class GuiSD:
 
 def dynamic_gpu_duration(func, duration, *args):
 
-    @torch.inference_mode()
     @spaces.GPU(duration=duration)
     def wrapped_func():
         yield from func(*args)

modutils.py

@@ -332,7 +332,7 @@ def save_gallery_history(images, files, history_gallery, history_files, progress
 
 def save_image_history(image, gallery, files, model_name: str, progress=gr.Progress(track_tqdm=True)):
     basename = f"{model_name.split('/')[-1]}_{datetime.now(FILENAME_TIMEZONE).strftime('%Y%m%d_%H%M%S')}"
-    if image is None or not isinstance(image, (str, Image.Image, np.array, tuple)): return gr.update(), gr.update()
+    if image is None or not isinstance(image, (str, Image.Image, np.ndarray, tuple)): return gr.update(), gr.update()
     if not gallery: gallery = []
     if not files: files = []
     filename = f"{basename}.png"
@@ -341,7 +341,7 @@ def save_image_history(image, gallery, files, model_name: str, progress=gr.Progr
     elif isinstance(image, Image.Image):
         oldpath = "temp.png"
         image.save(oldpath)
-    elif isinstance(image, np.array):
+    elif isinstance(image, np.ndarray):
         oldpath = "temp.png"
         Image.fromarray(image).convert('RGBA').save(oldpath)
     newpath = oldpath