code: def test_fillna_object_edgecase_feature_generator(
      generator_helper, data_helper
  ):
      # Given
      input_data = data_helper.generate_int_feature().to_frame(
          "int_as_object"
      )
      input_data = input_data.astype("object")
      edge_case_input = copy.deepcopy(input_data)
      input_data.loc[0] = np.nan
      expected_output_data = copy.deepcopy(input_data)
      expected_output_data.loc[0] = ""
  
      generator = FillNaFeatureGenerator()
  
      expected_feature_metadata_in_full = {
          ("object", ()): ["int_as_object"],
      }
  
      expected_feature_metadata_full = expected_feature_metadata_in_full
  
      # When
      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,
      )
  
      edge_case_output = generator.transform(edge_case_input)
  
      assert expected_output_data.equals(output_data)
      assert edge_case_input.equals(edge_case_output)
  
imports: import copy
  import numpy
  from autogluon.features.generators import FillNaFeatureGenerator
label_desc: Use image node_id 2 for calling a global function with example usage: test_fillna_object_edgecase_feature_generator(generator_helper, data_helper) without return types