code: def test_partial_fit_errors():
      # Test partial_fit error handling.
      X = [[3, 2], [1, 6]]
      y = [1, 0]
  
      # no classes passed
      with pytest.raises(ValueError):
          MLPClassifier(solver="sgd").partial_fit(X, y, classes=[2])
  
      # lbfgs doesn't support partial_fit
      assert not hasattr(MLPClassifier(solver="lbfgs"), "partial_fit")
  
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 15 for calling a global function with example usage: test_partial_fit_errors() without return types