code: def test_gam_nonNeg_coeffs():
      print(
          "Checking logloss for binomial with different scale parameters"
      )
      h2o_data = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/glm_test/binomial_20_cols_10KRows.csv"
          )
      )
      h2o_data["C1"] = h2o_data["C1"].asfactor()
      h2o_data["C2"] = h2o_data["C2"].asfactor()
      myY = "C21"
      h2o_data["C21"] = h2o_data["C21"].asfactor()
      buildModelCheckCoeff(
          h2o_data, myY, ["C11", "C12", "C13"], "binomial"
      )
  
      print("Checking mse for gaussian with different scale parameters")
      h2o_data = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/glm_test/gaussian_20cols_10000Rows.csv"
          )
      )
      h2o_data["C1"] = h2o_data["C1"].asfactor()
      h2o_data["C2"] = h2o_data["C2"].asfactor()
      myY = "C21"
      buildModelCheckCoeff(
          h2o_data, myY, ["C11", "C12", "C13"], "gaussian"
      )
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gam import H2OGeneralizedAdditiveEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_gam_nonNeg_coeffs() without return types