code: def save_load_model():
      training_data = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/benign.csv")
      )
  
      Y = 3
      X = list(range(3)) + list(range(4, 11))
  
      model = H2OGeneralizedLinearEstimator(
          model_id="original_id",
          family="binomial",
          alpha=0,
          Lambda=1e-5,
      )
      model.train(x=X, y=Y, training_frame=training_data)
      assert model.model_id == "original_id"
      model.model_id = "new_id"
      assert model.model_id == "new_id"
  
imports: import h2o
  from h2o.estimators.estimator_base import H2OEstimator
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: save_load_model() without return types