code: def _predict(self, data):
      pred = self.model.predict(data.X_test)
      metric = self.eval(data, pred)
      return metric
  
file_path: thundergbm/python/benchmarks/model/thundergbm_model.py
imports: from model.base_model import BaseModel
  import thundergbm
  import time
  import numpy
  import utils.data_utils
  from model.datasets import Dataset
label_desc: Use image node_id 4 for calling the ThunderGBMModel obj's underlying member method code with example usage: obj._predict(data) and returns: metric