code: def test_tabu() -> None:
      num_tests = 97
      for o in ["DiscreteOnePlusOne"]:
          values = []
          valuesT = []
          for _ in range(num_tests):
              dim = 4
              arity = 7
              budget = (arity**dim) // 50
              domain = ng.p.TransitionChoice(
                  range(arity), ordered=False, repetitions=dim
              )
              optimum = np.random.randint(arity, size=dim)
  
              def of(x):
                  return -np.sum((np.asarray(x) == optimum))
  
              recom = (
                  ng.optimizers.registry[o](domain, budget)
                  .minimize(of)
                  .value
              )
              recomT = (
                  ng.optimizers.registry[o + "T"](domain, budget)
                  .minimize(of)
                  .value
              )
              values += [of(recom)]
              valuesT += [of(recomT)]
          pval = stats.mannwhitneyu(
              valuesT, values, alternative="less"
          ).pvalue
          assert (
              pval < 0.15
          ), f"{o} fails the Tabu search test: pval = {pval}."
  
file_path: nevergrad/nevergrad/optimization/test_tabu.py
imports: import pytest
  import numpy
  import sys
  from scipy import stats
  import nevergrad
  import nevergrad.common.typing
label_desc: Use image node_id 1 for calling a global function with example usage: test_tabu() and returns: unknown