code: def test_gbrt_in_parallel():
      # check estimate quantiles with parallel
      rng = np.random.RandomState(1)
      N = 10000
      X = np.ones((N, 1))
      y = rng.normal(size=N)
  
      rgr = GradientBoostingQuantileRegressor(
          n_jobs=1, random_state=np.random.RandomState(1)
      )
      rgr.fit(X, y)
      estimates = rgr.predict(X)
  
      rgr.set_params(n_jobs=2, random_state=np.random.RandomState(1))
      rgr.fit(X, y)
      estimates_parallel = rgr.predict(X)
  
      assert_array_equal(estimates, estimates_parallel)
  
file_path: scikit-optimize/skopt/learning/tests/test_gbrt.py
imports: import numpy
  import pytest
  from scipy import stats
  from sklearn.ensemble import GradientBoostingRegressor
  from sklearn.ensemble import RandomForestRegressor
  from numpy.testing import assert_equal
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_almost_equal
  from skopt.learning import GradientBoostingQuantileRegressor
label_desc: Use image node_id 5 for calling a global function with example usage: test_gbrt_in_parallel() without return types