code: def test_gam_dual_mode_multinomial():
      train = h2o.import_file(
          pyunit_utils.locate(
              "smalldata/glm_test/multinomial_10_classes_10_cols_10000_Rows_train.csv"
          )
      )
      train["C11"] = train["C11"].asfactor()
      train["C1"] = train["C1"].asfactor()
      train["C2"] = train["C2"].asfactor()
      test = h2o.import_file(
          pyunit_utils.locate(
              "smalldata/glm_test/multinomial_10_classes_10_cols_10000_Rows_train.csv"
          )
      )
      test["C11"] = test["C11"].asfactor()
      test["C1"] = test["C1"].asfactor()
      test["C2"] = test["C2"].asfactor()
      x = ["C1", "C2"]
      y = "C11"
      gam_cols1 = ["C6", ["C7", "C8"], "C9", "C10"]
      gam_cols2 = [["C6"], ["C7", "C8"], ["C9"], ["C10"]]
      h2o_model1 = H2OGeneralizedAdditiveEstimator(
          family="multinomial",
          gam_columns=gam_cols1,
          bs=[1, 1, 0, 0],
          max_iterations=2,
          seed=1,
      )
      h2o_model1.train(
          x=x, y=y, training_frame=train, validation_frame=test
      )
      h2o_model2 = H2OGeneralizedAdditiveEstimator(
          family="multinomial",
          gam_columns=gam_cols2,
          bs=[1, 1, 0, 0],
          max_iterations=2,
          seed=1,
      )
      h2o_model2.train(
          x=x, y=y, training_frame=train, validation_frame=test
      )
      # check that both models produce the same coefficients
      print(h2o_model1.coef())
      print(h2o_model2.coef())
      pyunit_utils.assertCoefDictEqual(
          h2o_model1.coef()["coefficients"],
          h2o_model2.coef()["coefficients"],
          tol=1e-6,
      )
      # check both models product the same validation metrics
      assert (
          abs(
              h2o_model1.logloss(valid=True)
              - h2o_model2.logloss(valid=True)
          )
          < 1e-6
      ), "Expected validation logloss: {0}, Actual validation logloss: {1}".format(
          h2o_model1.logloss(valid=True), h2o_model2.logloss(valid=True)
      )
  
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_dual_mode_multinomial() without return types