code: def test_mlp_warm_start_with_early_stopping(MLPEstimator):
      """Check that early stopping works with warm start."""
      mlp = MLPEstimator(
          max_iter=10,
          random_state=0,
          warm_start=True,
          early_stopping=True,
      )
      mlp.fit(X_iris, y_iris)
      n_validation_scores = len(mlp.validation_scores_)
      mlp.set_params(max_iter=20)
      mlp.fit(X_iris, y_iris)
      assert len(mlp.validation_scores_) > n_validation_scores
  
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 36 for calling a global function with example usage: test_mlp_warm_start_with_early_stopping(MLPEstimator) without return types