code: def test_mlp_partial_fit_after_fit(MLPEstimator):
      """Check partial fit does not fail after fit when early_stopping=True.
  
      Non-regression test for gh-25693.
      """
      mlp = MLPEstimator(early_stopping=True, random_state=0).fit(
          X_iris, y_iris
      )
  
      msg = "partial_fit does not support early_stopping=True"
      with pytest.raises(ValueError, match=msg):
          mlp.partial_fit(X_iris, y_iris)
  
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 38 for calling a global function with example usage: test_mlp_partial_fit_after_fit(MLPEstimator) without return types