code: def test_pipeline():
      """Check that SymbolicRegressor/Transformer can work in a pipeline"""
  
      # Check the regressor
      est = make_pipeline(
          StandardScaler(),
          SymbolicRegressor(
              population_size=50,
              generations=10,
              tournament_size=5,
              random_state=0,
          ),
      )
      est.fit(diabetes.data, diabetes.target)
      assert_almost_equal(
          est.score(diabetes.data, diabetes.target),
          -3.702070228336284,
          decimal=5,
      )
  
      # Check the classifier
      est = make_pipeline(
          StandardScaler(),
          SymbolicClassifier(
              population_size=50,
              generations=5,
              tournament_size=5,
              random_state=0,
          ),
      )
      est.fit(cancer.data, cancer.target)
      assert_almost_equal(
          est.score(cancer.data, cancer.target), 0.934973637961
      )
  
      # Check the transformer
      est = make_pipeline(
          SymbolicTransformer(
              population_size=50,
              hall_of_fame=20,
              generations=5,
              tournament_size=5,
              random_state=0,
          ),
          DecisionTreeRegressor(),
      )
      est.fit(diabetes.data, diabetes.target)
      assert_almost_equal(
          est.score(diabetes.data, diabetes.target), 1.0
      )
  
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 27 for calling a global function with example usage: test_pipeline() without return types