code: def test_partial_fit_unseen_classes():
      # Non regression test for bug 6994
      # Tests for labeling errors in partial fit
  
      clf = MLPClassifier(random_state=0)
      clf.partial_fit(
          [[1], [2], [3]], ["a", "b", "c"], classes=["a", "b", "c", "d"]
      )
      clf.partial_fit([[4]], ["d"])
      assert clf.score([[1], [2], [3], [4]], ["a", "b", "c", "d"]) > 0
  
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 13 for calling a global function with example usage: test_partial_fit_unseen_classes() without return types