code: def fit(self, xs, ys):
      x_train = np.array(xs, dtype=np.float32)
      y_train = np.array(ys, dtype=np.float32)
      y_max = np.max(y_train)
      y_train = y_train / max(y_max, 1e-9)
  
      index = np.random.permutation(len(x_train))
      dtrain = xgb.DMatrix(x_train[index], y_train[index])
  
      self.bst = xgb.train(self.xgb_params, dtrain)
  
imports: from .utils import *
label_desc: Use image node_id 2 for calling the XGBoostCostModel obj's underlying member method code with example usage: obj.fit(xs, ys) without return types