code: def test_debiasing_l1l2(mult_sparse_train_data, warm_debiasing):
      mult_sparse, mult_target = mult_sparse_train_data
      clf = CDClassifier(
          penalty="l1/l2",
          loss="squared_hinge",
          multiclass=False,
          debiasing=True,
          warm_debiasing=warm_debiasing,
          max_iter=20,
          C=0.01,
          random_state=0,
      )
      clf.fit(mult_sparse, mult_target)
      assert clf.score(mult_sparse, mult_target) > 0.75
      assert 0.0 <= clf.n_nonzero(percentage=True) <= 0.1
  
imports: import numpy
  import pytest
  from sklearn.datasets import load_digits
  from sklearn.preprocessing import LabelBinarizer
  from lightning.impl.primal_cd import CDClassifier, CDRegressor
  from lightning.impl.tests.utils import check_predict_proba
label_desc: Use image node_id 16 for calling a global function with example usage: test_debiasing_l1l2(mult_sparse_train_data, warm_debiasing) without return types