code: def test_multi_class_n_jobs(kernel):
      # Test that multi-class GPC produces identical results with n_jobs>1.
      gpc = GaussianProcessClassifier(kernel=kernel)
      gpc.fit(X, y_mc)
  
      gpc_2 = GaussianProcessClassifier(kernel=kernel, n_jobs=2)
      gpc_2.fit(X, y_mc)
  
      y_prob = gpc.predict_proba(X2)
      y_prob_2 = gpc_2.predict_proba(X2)
      assert_almost_equal(y_prob, y_prob_2)
  
imports: import warnings
  import numpy
  import pytest
  from scipy.optimize import approx_fprime
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.gaussian_process import GaussianProcessClassifier
  from sklearn.gaussian_process.kernels import RBF, CompoundKernel, WhiteKernel
  from sklearn.gaussian_process.kernels import ConstantKernel
  from sklearn.gaussian_process.tests._mini_sequence_kernel import MiniSeqKernel
  from sklearn.utils._testing import assert_almost_equal, assert_array_equal
label_desc: Use image node_id 12 for calling a global function with example usage: test_multi_class_n_jobs(kernel) without return types