code: def evaluate(active_learner, train, test):
      y_pred = active_learner.classifier.predict(train)
      y_pred_test = active_learner.classifier.predict(test)
  
      print(
          "Train accuracy: {:.2f}".format(
              f1_score(y_pred, train.y, average="micro")
          )
      )
      print(
          "Test accuracy: {:.2f}".format(
              f1_score(y_pred_test, test.y, average="micro")
          )
      )
      print("---")
  
label_desc: Use image node_id 1 for calling a global function with example usage: evaluate(active_learner, train, test) without return types