code: def test_boston_housing_parameter_stress_test(self):
      options = dict(
          max_depth=[1, 5],
          learning_rate=[0.1, 0.5],
          n_estimators=[1, 10],
          min_child_weight=[1, 2],
          max_delta_step=[0, 0.1],
          colsample_bytree=[1, 0.5],
          colsample_bylevel=[1, 0.5],
          scale_pos_weight=[1],
          objective=["reg:linear"],
      )
  
      # Make a cartesian product of all options
      product = itertools.product(*options.values())
      args = [dict(zip(options.keys(), p)) for p in product]
  
      print(
          "Testing a total of %s cases. This could take a while"
          % len(args)
      )
      for it, arg in enumerate(args):
          self._train_convert_evaluate_assert(arg)
  
imports: import unittest
  import pandas
  import itertools
  import pytest
  from coremltools._deps import _HAS_SKLEARN, _HAS_XGBOOST
  from coremltools.models.utils import evaluate_regressor, _macos_version, _is_macos
label_desc: Use image node_id 8 for calling the XgboostBoosterBostonHousingNumericTest obj's underlying member method code with example usage: obj.test_boston_housing_parameter_stress_test() without return types