code: def test_partial_fit_classes_error():
      # Tests that passing different classes to partial_fit raises an error
      X = [[3, 2]]
      y = [0]
      clf = MLPClassifier(solver="sgd")
      clf.partial_fit(X, y, classes=[0, 1])
      with pytest.raises(ValueError):
          clf.partial_fit(X, y, classes=[1, 2])
  
imports: import re
  import sys
  import warnings
  from io import StringIO
  import joblib
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_almost_equal, assert_array_equal
  from sklearn.datasets import load_digits, load_iris, make_multilabel_classification, make_regression
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.metrics import roc_auc_score
  from sklearn.neural_network import MLPClassifier, MLPRegressor
  from sklearn.preprocessing import LabelBinarizer, MinMaxScaler, scale
  from sklearn.utils._testing import ignore_warnings
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 11 for calling a global function with example usage: test_partial_fit_classes_error() without return types