code: def test_lfr_grid(new_german):
      """Test that the new LFR works in a grid search (and that debiasing
      results in improved statistical parity difference).
      """
      X, y = new_german
      lfr = LearnedFairRepresentations(
          "age", reconstruct_weight=0, max_iter=1000
      )
      params = {"fairness_weight": [50, 0]}
      min_disc = make_scorer(
          statistical_parity_difference, prot_attr="age"
      )
      clf = GridSearchCV(lfr, params, scoring=min_disc, cv=2)
      clf.fit(X, y)
  
      assert clf.best_params_ == {"fairness_weight": 50}
  
imports: import numpy
  import pandas
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import make_pipeline
  from aif360.algorithms.preprocessing import LFR
  from aif360.sklearn.preprocessing import LearnedFairRepresentations
  from aif360.sklearn.metrics import make_scorer, statistical_parity_difference
label_desc: Use image node_id 11 for calling a global function with example usage: test_lfr_grid(new_german) without return types