Update app.py

app.py

@@ -42,10 +42,9 @@ pipe = StableDiffusionXLControlNetImg2ImgPipeline.from_pretrained(
     use_safetensors=True,
     scheduler=scheduler,
 )
-pipe.enable_xformers_memory_efficient_attention()
+# pipe.enable_xformers_memory_efficient_attention()
 # pipe.enable_model_cpu_offload()
 pipe.enable_vae_tiling()
-apply_hidiffusion(pipe)
 
 compel = Compel(
     tokenizer=[pipe.tokenizer, pipe.tokenizer_2],
@@ -88,6 +87,7 @@ def predict(
     controlnet_end=1.0,
     progress=gr.Progress(track_tqdm=True),
 ):
+    apply_hidiffusion(pipe)
     if input_image is None:
         raise gr.Error("Please upload an image.")
     padded_image = pad_image(input_image).resize((1024, 1024)).convert("RGB")