code: def test_weights_warning():
      """
      In this test, I will introduce a validation frame with no weight but training frame with weights.  There should be
      a warning about this.
      """
      training_data = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/benign.csv")
      )
      test_data = h2o.import_file(
          pyunit_utils.locate("smalldata/logreg/benign.csv")
      )
  
      Y = 3
      X = [0, 1, 2, 4, 5, 6, 7, 8, 9, 10]
  
      weight = (
          pyunit_utils.random_dataset_real_only(
              nrow=training_data.nrows, ncol=1, misFrac=0
          )
      ).abs()
      weight.set_name(0, "weight_columns")
      training_data = training_data.cbind(weight)
  
      model = H2OGeneralizedLinearEstimator(
          family="binomial",
          alpha=0,
          lambda_=1e-5,
          weights_column="weight_columns",
      )
      model.train(
          x=X,
          y=Y,
          training_frame=training_data,
          validation_frame=test_data,
      )
  
      pyunit_utils.checkLogWeightWarning(
          "weight_columns", wantWarnMessage=True
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_weights_warning() without return types