code: def test_early_stopping():
      """Check that early stopping works"""
  
      est1 = SymbolicRegressor(
          population_size=100,
          generations=2,
          stopping_criteria=200,
          random_state=0,
      )
      est1.fit(diabetes.data[:400, :], diabetes.target[:400])
      assert len(est1._programs) == 1
  
      est1 = SymbolicTransformer(
          population_size=100,
          generations=2,
          stopping_criteria=100,
          random_state=0,
      )
      est1.fit(cancer.data[:400, :], cancer.target[:400])
      assert len(est1._programs) == 2
  
imports: import pickle
  import pytest
  import sys
  from io import StringIO
  import numpy
  from scipy.stats import pearsonr, spearmanr
  from sklearn.datasets import load_diabetes, load_breast_cancer
  from sklearn.metrics import mean_absolute_error
  from sklearn.model_selection import GridSearchCV
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.utils._testing import assert_almost_equal
  from sklearn.utils._testing import assert_array_equal
  from sklearn.utils._testing import assert_array_almost_equal
  from sklearn.utils._testing import assert_raises
  from sklearn.utils.validation import check_random_state
  from gplearn.genetic import SymbolicClassifier, SymbolicRegressor
  from gplearn.genetic import SymbolicTransformer
  from gplearn.fitness import weighted_pearson, weighted_spearman
  from gplearn._program import _Program
  from gplearn.fitness import _fitness_map
  from gplearn.functions import add2, sub2, mul2, div2, sqrt1, log1, abs1, max2, min2
  from gplearn.functions import _Function
label_desc: Use image node_id 19 for calling a global function with example usage: test_early_stopping() without return types