code: def test_string_target(pyplot):
      """Check that decision boundary works with classifiers trained on string labels."""
      iris = load_iris()
      X = iris.data[:, [0, 1]]
  
      # Use strings as target
      y = iris.target_names[iris.target]
      log_reg = LogisticRegression().fit(X, y)
  
      # Does not raise
      DecisionBoundaryDisplay.from_estimator(
          log_reg,
          X,
          grid_resolution=5,
          response_method="predict",
      )
  
imports: import warnings
  import numpy
  import pytest
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_multilabel_classification
  from sklearn.ensemble import IsolationForest
  from sklearn.inspection import DecisionBoundaryDisplay
  from sklearn.inspection._plot.decision_boundary import _check_boundary_response_method
  from sklearn.linear_model import LogisticRegression
  from sklearn.preprocessing import scale
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.utils._testing import assert_allclose, assert_array_equal
label_desc: Use image node_id 19 for calling a global function with example usage: test_string_target(pyplot) without return types