Update app.py

app.py

@@ -25,29 +25,29 @@ del vae
 pipe.force_zeros_for_empty_prompt = False
 negative_prompt= "Logo,Watermark,Text,Ugly,Morbid,Extra fingers,Poorly drawn hands,Mutation,Blurry,Extra limbs,Gross proportions,Missing arms,Mutated hands,Long neck,Duplicate,Mutilated,Mutilated hands,Poorly drawn face,Deformed,Bad anatomy,Cloned face,Malformed limbs,Missing legs,Too many fingers"
 
-print("Optimizing BRIA 2.2 HD - this could take a while")
-t=time.time()
-pipe.unet = torch.compile(
-    pipe.unet, mode="reduce-overhead", fullgraph=True # 600 secs compilation
-)
-with torch.no_grad():
-    outputs = pipe(
-        prompt="an apple",
-        num_inference_steps=30,
-        width=1536,
-        height=1536,
-        negative_prompt=negative_prompt
-    )
-
-    # This will avoid future compilations on different shapes
-    unet_compiled = torch._dynamo.run(pipe.unet)
-    unet_compiled.config=pipe.unet.config
-    unet_compiled.add_embedding = Dummy()
-    unet_compiled.add_embedding.linear_1 = Dummy()
-    unet_compiled.add_embedding.linear_1.in_features = pipe.unet.add_embedding.linear_1.in_features
-    pipe.unet = unet_compiled
-
-print(f"Optimizing finished successfully after {time.time()-t} secs")
+# print("Optimizing BRIA 2.2 HD - this could take a while")
+# t=time.time()
+# pipe.unet = torch.compile(
+#     pipe.unet, mode="reduce-overhead", fullgraph=True # 600 secs compilation
+# )
+# with torch.no_grad():
+#     outputs = pipe(
+#         prompt="an apple",
+#         num_inference_steps=30,
+#         width=1536,
+#         height=1536,
+#         negative_prompt=negative_prompt
+#     )
+
+#     # This will avoid future compilations on different shapes
+#     unet_compiled = torch._dynamo.run(pipe.unet)
+#     unet_compiled.config=pipe.unet.config
+#     unet_compiled.add_embedding = Dummy()
+#     unet_compiled.add_embedding.linear_1 = Dummy()
+#     unet_compiled.add_embedding.linear_1.in_features = pipe.unet.add_embedding.linear_1.in_features
+#     pipe.unet = unet_compiled
+
+# print(f"Optimizing finished successfully after {time.time()-t} secs")
 
 @spaces.GPU(enable_queue=True)
 def infer(prompt,seed,resolution):