code: def test_debiasing_warm_start(bin_dense_train_data):
      bin_dense, bin_target = bin_dense_train_data
      clf = CDClassifier(
          penalty="l1", max_iter=10, warm_start=True, random_state=0
      )
      clf.C = 0.5
      clf.fit(bin_dense, bin_target)
      assert clf.n_nonzero() == 74
      np.testing.assert_almost_equal(
          clf.score(bin_dense, bin_target), 1.0
      )
  
      clf.C = 1.0
      clf.fit(bin_dense, bin_target)
      # FIXME: not the same sparsity as without warm start...
      assert clf.n_nonzero() == 77
      np.testing.assert_almost_equal(
          clf.score(bin_dense, bin_target), 1.0
      )
  
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 17 for calling a global function with example usage: test_debiasing_warm_start(bin_dense_train_data) without return types