code: def test_oaa(self):
      X = [
          "1 | feature1:2.5",
          "2 | feature1:0.11 feature2:-0.0741",
          "3 | feature3:2.33 feature4:0.8 feature5:-3.1",
          "1 | feature2:-0.028 feature1:4.43",
          "2 | feature5:1.532 feature6:-3.2",
      ]
      model = VW(convert_to_vw=False, oaa=3, loss_function="logistic")
      model.fit(X)
      prediction = model.predict(X)
      assert np.allclose(prediction, [1.0, 2.0, 3.0, 1.0, 2.0])
  
imports: from collections import namedtuple
  import os
  import numpy
  from packaging import version
  import pandas
  import pytest
  from scipy.sparse import csr_matrix
  from sklearn import datasets, __version__
  from sklearn.model_selection import KFold
  from sklearn.utils.estimator_checks import check_estimator
  from vowpalwabbit.sklearn import VW, VWClassifier, VWRegressor, tovw, VWMultiClassifier, VWRegressor
label_desc: Use image node_id 9 for calling the TestVW obj's underlying member method code with example usage: obj.test_oaa() without return types