code: def buildModelCheckCoeff(train_data, y, gamX, family):
      numKnots = [3, 4, 5]
      x = ["C1", "C2"]
      h2o_model = H2OGeneralizedAdditiveEstimator(
          family=family,
          gam_columns=gamX,
          scale=[0.001, 0.001, 0.001],
          bs=[2, 2, 2],
          spline_orders=[2, 3, 4],
          num_knots=numKnots,
      )
      h2o_model.train(x=x, y=y, training_frame=train_data)
      # check to make sure gam column coefficients are non-negative
      coef_dict = h2o_model.coef()
      coef_keys = coef_dict.keys()
      for key in coef_keys:
          if "center" in key:
              assert coef_dict[key] >= 0
  
imports: import sys
  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: buildModelCheckCoeff(train_data, y, gamX, family) without return types