Update app.py

app.py

@@ -60,18 +60,18 @@ def generate(
             
         if not use_img2img:
             pipe = DiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16)
-            pipe.unet.set_default_attn_processor()
+
             if use_vae:  
                 vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
                 pipe = DiffusionPipeline.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
-                pipe.unet.set_default_attn_processor()
+
         if use_img2img:
             pipe = AutoPipelineForImage2Image.from_pretrained(model, torch_dtype=torch.float16)
-            pipe.unet.set_default_attn_processor()
+
             if use_vae:  
                 vae = AutoencoderKL.from_pretrained(vaecall, torch_dtype=torch.float16)
                 pipe = AutoPipelineForImage2Image.from_pretrained(model, vae=vae, torch_dtype=torch.float16)
-                pipe.unet.set_default_attn_processor()
+
             response = requests.get(url)
             init_image = Image.open(BytesIO(response.content)).convert("RGB")
             init_image = init_image.resize((width, height))
@@ -82,6 +82,8 @@ def generate(
             
         else:
             pipe.to(device)
+            pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+            pipe.unet.set_default_attn_processor()
         
     generator = torch.Generator().manual_seed(seed)