code: def test_regression():
      print("Regression tests")
      name = "gaussian"
      print("Create default", name, "model")
      (model, f_test) = regression_model_default(
          H2OGradientBoostingEstimator, name
      )
      print("Create custom ", name, "model")
      (model2, f_test2) = regression_model_distribution(
          H2OGradientBoostingEstimator,
          upload_distribution(CustomDistributionGaussian, name),
      )
  
      check_model_metrics(model, model2, name)
  
      print(
          "Test scoring history is without deviance if custom distribution is set."
      )
      sh = model.scoring_history().columns
      shc = model2.scoring_history().columns
      assert (
          "training_deviance" in sh and "training_deviance" not in shc
      )
  
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 3 for calling a global function with example usage: test_regression() without return types