code: def test_repair0():
      ad = AdultDataset(
          protected_attribute_names=["sex"],
          privileged_classes=[["Male"]],
          categorical_features=[],
          features_to_keep=["age", "education-num"],
      )
  
      di = DisparateImpactRemover(repair_level=0.0)
      ad_repd = di.fit_transform(ad)
  
      assert ad_repd == ad
  
file_path: AIF360/tests/test_disparate_impact_remover.py
imports: import numpy
  from sklearn.linear_model import LogisticRegression
  from sklearn.svm import SVC
  from sklearn.preprocessing import MinMaxScaler
  from aif360.algorithms.preprocessing import DisparateImpactRemover
  from aif360.datasets import AdultDataset
  from aif360.metrics import ClassificationMetric
label_desc: Use image node_id 1 for calling a global function with example usage: test_repair0() without return types