code: def test_cascade_binary(fit_helper):
      fit_args = dict(
          hyperparameters={
              LGBModel: {},
              TabularNeuralNetTorchModel: {},
          },
      )
      dataset_name = "adult"
      cascade = ["LightGBM", "WeightedEnsemble_L2"]
      fit_helper.fit_and_validate_dataset_with_cascade(
          dataset_name=dataset_name,
          fit_args=fit_args,
          cascade=cascade,
          expected_model_count=3,
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_cascade_binary(fit_helper) without return types