Update app.py

app.py

@@ -61,11 +61,6 @@ canny = CannyDetector()
 anyline = AnylineDetector.from_pretrained("TheMistoAI/MistoLine", filename="MTEED.pth", subfolder="Anyline")
 open_pose = OpenposeDetector.from_pretrained("lllyasviel/Annotators")
 
-torch.backends.cuda.matmul.allow_tf32 = True
-pipe.vae.enable_tiling()
-pipe.vae.enable_slicing()
-pipe.enable_model_cpu_offload() # for saving memory
-
 def convert_from_image_to_cv2(img: Image) -> np.ndarray:
     return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
 
@@ -147,7 +142,7 @@ def resize_img(input_image, max_side=1024, min_side=768, size=None,
 
 @spaces.GPU(duration=180)
 def infer(cond_in, image_in, prompt, inference_steps, guidance_scale, control_mode, control_strength, control_guidance_end, seed, progress=gr.Progress(track_tqdm=True)):
-            
+    print('infer')      
     if cond_in is None:
         if image_in is not None:
             image_in = resize_img(load_image(image_in))
@@ -165,7 +160,8 @@ def infer(cond_in, image_in, prompt, inference_steps, guidance_scale, control_mo
         control_image = resize_img(load_image(cond_in))
 
     width, height = control_image.size
-    
+
+    print('pipe ...')
     image = pipe(
         prompt, 
         control_image=[control_image],
@@ -177,8 +173,7 @@ def infer(cond_in, image_in, prompt, inference_steps, guidance_scale, control_mo
         guidance_scale=guidance_scale,
         generator=torch.manual_seed(seed),
     ).images[0]
-
-    torch.cuda.empty_cache() 
+    print('pipe DONE')
     
     return image, control_image, gr.update(visible=True)