code: def _predict(self, data):
      # test dataset for catboost
      cb_test = cb.Pool(data.X_test, data.y_test)
      if data.task == "Ranking":
          cb_test.set_group_id(data.groups)
      preds = self.model.predict(cb_test)
      metric = self.eval(data, preds)
  
      return metric
  
file_path: thundergbm/python/benchmarks/model/catboost_model.py
imports: from model.base_model import BaseModel
  import numpy
  import catboost
  import time
  import utils.data_utils
  from model.datasets import Dataset
label_desc: Use image node_id 4 for calling the CatboostModel obj's underlying member method code with example usage: obj._predict(data) and returns: metric