Update app.py

app.py

@@ -62,27 +62,23 @@ def generate(
             pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16) 
             pipe.enable_sequential_cpu_offload()
             pipe.unet.set_default_attn_processor()
-            pipe.enable_vae_slicing()
 
             if use_vae:  
                 vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
                 pipe = DiffusionPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
                 pipe.enable_sequential_cpu_offload()
                 pipe.unet.set_default_attn_processor()
-                pipe.enable_vae_slicing()
 
         if use_img2img:
             pipe = AutoPipelineForImage2Image.from_pretrained(model, torch_dtype=torch.float16)
             pipe.enable_sequential_cpu_offload()
             pipe.unet.set_default_attn_processor()
-            pipe.enable_vae_slicing()
             
             if use_vae:  
                 vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
                 pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
                 pipe.enable_sequential_cpu_offload()
                 pipe.unet.set_default_attn_processor()
-                pipe.enable_vae_slicing()
 
             response = requests.get(url)
             init_image = Image.open(BytesIO(response.content)).convert("RGB")