2345

app.py

@@ -24,10 +24,12 @@ def load_model(model_path, device):
 
 def load_secure_model(model):
     print("Compiling secure model...")
-    secure_model = compile_torch_model(model.to("cpu"), 
-                                     n_bits={"model_inputs": 4, "op_inputs": 3, "op_weights": 3, "model_outputs": 5},
-                                     rounding_threshold_bits={"n_bits": 7},
-                                     torch_inputset=torch.rand(10, 3, 224, 224))
+    secure_model = compile_torch_model(
+        model.to("cpu"), 
+        n_bits={"model_inputs": 4, "op_inputs": 3, "op_weights": 3, "model_outputs": 5},
+        rounding_threshold_bits={"n_bits": 7, "method": "APPROXIMATE"},
+        torch_inputset=torch.rand(10, 3, 224, 224)
+    )
     return secure_model
 
 # Image preprocessing (match with the transforms used during training)