code: def test_lfr_models(old_lfr, new_lfr):
      """Test that the learned model parameters of the old and new LFR match."""
      assert np.allclose(old_lfr.w, new_lfr.coef_.flatten())
      assert np.allclose(old_lfr.prototypes, new_lfr.prototypes_)
  
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 8 for calling a global function with example usage: test_lfr_models(old_lfr, new_lfr) without return types