code: def test_multinomial_no_elemwise_update(self):
      with pm.Model() as m:
          batched_dist = pm.Multinomial(
              "batched_dist", n=5, p=np.ones(4) / 4, shape=(10, 4)
          )
          with pytensor.config.change_flags(
              mode=fast_unstable_sampling_mode
          ):
              step = pm.Metropolis([batched_dist])
              assert not step.elemwise_update
  
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 TestMetropolis obj's underlying member method code with example usage: obj.test_multinomial_no_elemwise_update() without return types