code: def main():
      # Load dataset
      data, labels = datasets.load_breast_cancer(return_X_y=True)
      # Split into train and test set
      train_x, test_x, train_y, test_y = train_test_split(
          data, labels, test_size=0.25
      )
  
      train_set = RayDMatrix(train_x, train_y)
      test_set = RayDMatrix(test_x, test_y)
  
      # Set config
      config = {
          "objective": "binary",
          "metric": ["binary_logloss", "binary_error"],
          "max_depth": 3,
      }
  
      evals_result = {}
  
      # Train the classifier
      bst = train(
          config,
          train_set,
          evals=[(test_set, "eval")],
          evals_result=evals_result,
          ray_params=RayParams(max_actor_restarts=1, num_actors=1),
          verbose_eval=False,
      )
  
      bst.booster_.save_model("simple.lgbm")
      print(
          "Final validation error: {:.4f}".format(
              evals_result["eval"]["binary_error"][-1]
          )
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types