code: def build_assert_monotone_output(
      train_file,
      test_file,
      x,
      target,
      gam_columns,
      num_knot,
      bs_choice,
      spline_order,
  ):
      train_data = h2o.import_file(train_file)
      test_data = h2o.import_file(test_file)
      h2o_model2 = H2OGeneralizedAdditiveEstimator(
          family="gaussian",
          gam_columns=gam_columns,
          num_knots=num_knot,
          spline_orders=spline_order,
          splines_non_negative=[True],
          bs=bs_choice,
      )
      h2o_model2.train(x=x, y=target, training_frame=train_data)
      pred_frame = h2o_model2.predict(test_data)
      assertMonotonePrediction(pred_frame)
  
imports: import sys, os
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.gam import H2OGeneralizedAdditiveEstimator
label_desc: Use image node_id 2 for calling a global function with example usage: build_assert_monotone_output(train_file, test_file, x, target, gam_columns, num_knot, bs_choice, spline_order) without return types