code: def test_pareto_experiment() -> None:
      # Checking MOO in cross-validation.
      objective_functions: tp.List[tp.Any] = [
          ArtificialFunction("sphere", block_dimension=7),
          ArtificialFunction("sphere", block_dimension=7),
          ArtificialFunction("cigar", block_dimension=7),
      ]
      xps = helpers.SpecialEvaluationExperiment.create_crossvalidation_experiments(
          objective_functions, pareto_size=16
      )
      assert len(xps) == 15  # 3 xps, multiplied by 5 Pareto extractors
      param = xps[0].parametrization
      out = xps[0](*param.args, **param.kwargs)
      assert isinstance(out, np.ndarray) and out.size == 2
      param._losses = out  # hack for testing
      evaluation = xps[0].evaluation_function(param, param, param)
      assert isinstance(evaluation, float)
  
imports: import pickle
  import numpy
  import pytest
  import nevergrad
  from nevergrad.common import testing
  from nevergrad.functions import ArtificialFunction
  import nevergrad.common.typing
  from .None import base
  from .None import helpers
label_desc: Use image node_id 11 for calling a global function with example usage: test_pareto_experiment() without return types