code: def test_verbose_sgd():
      # Test verbose.
      X = [[3, 2], [1, 6]]
      y = [1, 0]
      clf = MLPClassifier(
          solver="sgd", max_iter=2, verbose=10, hidden_layer_sizes=2
      )
      old_stdout = sys.stdout
      sys.stdout = output = StringIO()
  
      with ignore_warnings(category=ConvergenceWarning):
          clf.fit(X, y)
      clf.partial_fit(X, y)
  
      sys.stdout = old_stdout
      assert "Iteration" in output.getvalue()
  
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 23 for calling a global function with example usage: test_verbose_sgd() without return types