code: def setup_class(cls):
      # here we do not need to check convergence from default start_params
      start_params = [
          14.1709,
          0.7085,
          -3.4548,
          -0.539,
          3.2368,
          -7.9299,
          -5.0529,
      ]
      mod_poi = Poisson(endog, exog)
      res_poi = mod_poi.fit(start_params=start_params)
      marge_poi = res_poi.get_margeff(dummy=True)
      cls.res = res_poi
      cls.margeff = marge_poi
  
      cls.res1_slice = [0, 1, 2, 3, 5, 6]
      cls.res1 = res_stata.results_poisson_margins_dummy
  
imports: import numpy
  from numpy.testing import assert_allclose
  from statsmodels.datasets.cpunish import load
  from statsmodels.discrete.discrete_model import NegativeBinomial, NegativeBinomialP, Poisson
  import statsmodels.discrete.tests.results.results_count_margins
  from statsmodels.tools.tools import add_constant
label_desc: Use image node_id 1 for calling the TestPoissonMarginDummy obj's underlying member method code with example usage: obj.setup_class(cls) without return types