code: def test_warm_start_full_iteration(MLPEstimator):
      # Non-regression test for:
      # https://github.com/scikit-learn/scikit-learn/issues/16812
      # Check that the MLP estimator accomplish `max_iter` with a
      # warm started estimator.
      X, y = X_iris, y_iris
      max_iter = 3
      clf = MLPEstimator(
          hidden_layer_sizes=2,
          solver="sgd",
          warm_start=True,
          max_iter=max_iter,
      )
      clf.fit(X, y)
      assert max_iter == clf.n_iter_
      clf.fit(X, y)
      assert max_iter == clf.n_iter_
  
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 27 for calling a global function with example usage: test_warm_start_full_iteration(MLPEstimator) without return types