code: def test_default_boston_iterative_fit(self):
      if self.__class__ == BaseRegressionComponentTest:
          return
  
      if not hasattr(self.module, "iterative_fit"):
          return
  
      for i in range(2):
          with ignore_warnings(regressor_warnings):
              (
                  predictions,
                  targets,
                  regressor,
              ) = _test_regressor_iterative_fit(
                  dataset="boston", Regressor=self.module
              )
  
          score = sklearn.metrics.r2_score(targets, predictions)
          fixture = self.res["default_boston_iterative"]
          places = self.res.get("default_boston_iterative_places", 7)
  
          if score < -1e10:
              print(f"score = {score}, fixture = {fixture}")
              score = np.log(-score)
              fixture = np.log(-fixture)
  
          self.assertAlmostEqual(fixture, score, places)
  
          if self.step_hyperparameter is not None:
              param_name = self.step_hyperparameter["name"]
              default = self.step_hyperparameter["value"]
  
              value = getattr(regressor.estimator, param_name)
              expected = self.res.get(
                  "boston_iterative_n_iter", default
              )
  
              # To currently allow for MLPRegressor which is indeterministic,
              # we can have multiple values
              if isinstance(expected, Container):
                  assert value in expected
              else:
                  assert value == expected
  
imports: from typing import Container, Type
  import numpy
  import sklearn.metrics
  from autosklearn.pipeline.components.regression import RegressorChoice, _regressors
  from autosklearn.pipeline.components.regression.libsvm_svr import LibSVM_SVR
  from autosklearn.pipeline.constants import SPARSE
  from autosklearn.pipeline.util import _test_regressor, _test_regressor_iterative_fit
  import pytest
  import unittest
  from test.test_pipeline.ignored_warnings import ignore_warnings, regressor_warnings
label_desc: Use image node_id 2 for calling the BaseRegressionComponentTest obj's underlying member method code with example usage: obj.test_default_boston_iterative_fit() without return types