code: def test_l1l2_multiclass_log_loss_no_linesearch(
      mult_sparse_train_data,
  ):
      mult_sparse, mult_target = mult_sparse_train_data
      clf = CDClassifier(
          penalty="l1/l2",
          loss="log",
          multiclass=True,
          selection="uniform",
          max_steps=0,
          max_iter=30,
          C=1.0,
          random_state=0,
      )
      clf.fit(mult_sparse, mult_target)
      np.testing.assert_almost_equal(
          clf.score(mult_sparse, mult_target), 0.88, 3
      )
      nz = np.sum(clf.coef_ != 0)
      assert nz == 297
  
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 22 for calling a global function with example usage: test_l1l2_multiclass_log_loss_no_linesearch(mult_sparse_train_data) without return types