Update app.py

app.py

@@ -10,8 +10,6 @@ if not torch.cuda.is_available():
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
-USE_TORCH_COMPILE = "1"
-ENABLE_CPU_OFFLOAD = "1"
 
 if torch.cuda.is_available():
     pipe = AutoPipelineForText2Image.from_pretrained(
@@ -21,6 +19,8 @@ if torch.cuda.is_available():
         add_watermarker=False
     )
     pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
+    pipe.unet = torch.compile(pipe.unet, mode="max-autotune", fullgraph=True)
+    pipe.vae.decode = torch.compile(pipe.vae.decode, mode="max-autotune", fullgraph=True)
     pipe.to("cuda")
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: