code: def test_bias_amplification_binary_groups():
      metric = ClassificationMetric(adult_test, adult_pred)
      bias_amp = metric.differential_fairness_bias_amplification()
      eps_data = (
          dataset_metric.smoothed_empirical_differential_fairness()
      )
      eps_clf = (
          classifier_metric.smoothed_empirical_differential_fairness()
      )
      assert bias_amp == (eps_clf - eps_data)
  
file_path: AIF360/tests/test_differential_fairness.py
imports: import numpy
  from sklearn.preprocessing import StandardScaler
  from sklearn.linear_model import LogisticRegression
  from aif360.datasets import AdultDataset
  from aif360.metrics import BinaryLabelDatasetMetric, ClassificationMetric
label_desc: Use image node_id 3 for calling a global function with example usage: test_bias_amplification_binary_groups() without return types