code: def test_competence(self, variable, has_grad, outcome):
      with pm.Model() as pmodel:
          pm.Normal("n", 0, 2, size=(3,))
          pm.Binomial("b", n=2, p=0.3)
      assert (
          DEMetropolisZ.competence(pmodel[variable], has_grad=has_grad)
          == outcome
      )
  
imports: import warnings
  import arviz
  import numpy
  import numpy.testing
  import pytensor
  import pytest
  import pymc
  from pymc.step_methods.metropolis import BinaryGibbsMetropolis, CategoricalGibbsMetropolis, DEMetropolis, DEMetropolisZ, Metropolis, MultivariateNormalProposal, NormalProposal
  from pymc.testing import fast_unstable_sampling_mode
  from tests import sampler_fixtures
  from tests.helpers import RVsAssignmentStepsTester, StepMethodTester
  from tests.models import mv_simple, mv_simple_discrete, simple_categorical
label_desc: Use image node_id 6 for calling the TestDEMetropolisZ obj's underlying member method code with example usage: obj.test_competence(variable, has_grad, outcome) without return types