Update app.py

app.py

@@ -102,13 +102,13 @@ if st.button("Run evolution"):
             net.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
             net.build(input_shape=(None, 10))  # Compile the model before training
             net.fit(X_train, y_train, epochs=10, verbose=0)
-            loss, acc = net.evaluate(X
-
-        loss, acc = net.evaluate(X_test, y_test, verbose=0)
+            loss, acc = net.evaluate(X_test, y_test, verbose=0)
         accuracy.append(acc)
     final_accuracy.append(np.mean(accuracy))
 st.write(f"Final accuracy: {np.mean(final_accuracy)}")
 
+        
+
 # Trade populations between tasks
 for i in range(num_tasks):
     for j in range(i+1, num_tasks):