code: def test_dummy_feature_generator(generator_helper, data_helper):
      # Given
      input_data = data_helper.generate_multi_feature_full()
  
      generator = DummyFeatureGenerator()
  
      expected_feature_metadata_in_full = {}
      expected_feature_metadata_full = {("int", ()): ["__dummy__"]}
  
      output_data = generator_helper.fit_transform_assert(
          input_data=input_data,
          generator=generator,
          expected_feature_metadata_in_full=expected_feature_metadata_in_full,
          expected_feature_metadata_full=expected_feature_metadata_full,
      )
  
      assert output_data.equals(
          DataFrame(
              data=[0, 0, 0, 0, 0, 0, 0, 0, 0], columns=["__dummy__"]
          )
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_dummy_feature_generator(generator_helper, data_helper) without return types