code: def test_ate(self, generate_regression_data):
      y, X, treatment, tau, b, e = generate_regression_data(mode=2)
      ctree = self.prepare_model()
      ate, ate_lower, ate_upper = ctree.estimate_ate(
          X=X, y=y, treatment=treatment
      )
      assert (ate >= ate_lower) and (ate <= ate_upper)
      assert ape(tau.mean(), ate) < ERROR_THRESHOLD
  
imports: import multiprocessing
  from abc import abstractmethod
  import pandas
  import pytest
  from sklearn.model_selection import train_test_split
  from causalml.inference.tree import CausalTreeRegressor, CausalRandomForestRegressor
  from causalml.metrics import ape
  from causalml.metrics import qini_score
  from .const import RANDOM_SEED, ERROR_THRESHOLD
label_desc: Use image node_id 5 for calling the TestCausalTreeRegressor obj's underlying member method code with example usage: obj.test_ate(generate_regression_data) without return types