code: def test_adagrad_hinge_multiclass(train_data):
      X, y = train_data
      clf = AdaGradClassifier(
          alpha=1e-2, n_iter=100, loss="hinge", random_state=0
      )
      clf.fit(X, y)
      assert not hasattr(clf, "predict_proba")
      np.testing.assert_almost_equal(clf.score(X, y), 0.940, 3)
  
file_path: lightning/lightning/impl/tests/test_adagrad.py
imports: import numpy
  import pytest
  from lightning.classification import AdaGradClassifier
  from lightning.regression import AdaGradRegressor
  from lightning.impl.adagrad_fast import _proj_elastic_all
  from lightning.impl.tests.utils import check_predict_proba
label_desc: Use image node_id 4 for calling a global function with example usage: test_adagrad_hinge_multiclass(train_data) without return types