code: def test_ovo():
      X = np.array([[0, 0, 1, 1], [1, 1, 0, 0], [-1, -1, -1, -1]] * 100)
      y = np.array([0, 1, 2] * 100)
      ovo = DistOneVsOneClassifier(
          LogisticRegression(solver="liblinear")
      )
      ovo.fit(X, y)
      preds = ovo.predict(X[:3])
      assert np.allclose(preds, np.array([0, 1, 2]))
  
label_desc: Use image node_id 3 for calling a global function with example usage: test_ovo() without return types