Update app.py

app.py

@@ -62,16 +62,17 @@ model.load_state_dict(torch.load(model_weights_path))
 # Set the model to evaluation mode for inference
 model.eval()
 
-# Create a NeuralNetClassifier using the loaded model
-cnn = NeuralNetClassifier(
-    module=model,
-    max_epochs=0,  # Set max_epochs to 0 to avoid additional training
-    lr=0.002,  # You can set this to the learning rate used during training
-    optimizer=torch.optim.Adam,  # You can set the optimizer used during training
-    device='cpu'  # You can specify the device ('cpu' for CPU, 'cuda' for GPU, etc.)
-)
-
-cnn.fit(XCnn_train, y_train)
+# # Create a NeuralNetClassifier using the loaded model
+# cnn = NeuralNetClassifier(
+#     module=model,
+#     max_epochs=0,  # Set max_epochs to 0 to avoid additional training
+#     lr=0.002,  # You can set this to the learning rate used during training
+#     optimizer=torch.optim.Adam,  # You can set the optimizer used during training
+#     device='cpu'  # You can specify the device ('cpu' for CPU, 'cuda' for GPU, etc.)
+# )
+
+# cnn.fit(XCnn_train, y_train)
+cnn = model