code: def test_worng_and_inherited_regression():
      print("Create default gaussian model")
      (model, f_test) = regression_model_default(
          H2OGradientBoostingEstimator, "gaussian"
      )
  
      print("Create custom wrong gaussian model")
      (model2, f_test2) = regression_model_distribution(
          H2OGradientBoostingEstimator,
          upload_distribution(
              CustomDistributionGaussianWrong, "gaussian_w"
          ),
      )
      assert model.rmse(valid=False) != model2.rmse(
          valid=False
      ), "Training rmse is not different for default and custom gaussian model."
      assert model.rmse(valid=True) != model2.rmse(
          valid=True
      ), "Validation rmse is not different for default and custom gaussian model."
  
      print("Create custom gaussian model without inheritance")
      (model3, f_test3) = regression_model_distribution(
          H2OGradientBoostingEstimator,
          upload_distribution(
              CustomDistributionGaussianNoInh, "gaussian_ni"
          ),
      )
      check_model_metrics(model, model3, "gaussian_ni")
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.utils.distributions import CustomDistributionGaussian, CustomDistributionBernoulli, CustomDistributionMultinomial, CustomDistributionGeneric
  from tests.pyunit_utils import regression_model_distribution, regression_model_default
  from tests.pyunit_utils import multinomial_model_default, multinomial_model_distribution
  from tests.pyunit_utils import binomial_model_default, binomial_model_distribution, check_model_metrics
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
label_desc: Use image node_id 7 for calling a global function with example usage: test_worng_and_inherited_regression() without return types