code: def setup_class(cls):
      cls.random_seed = 20160911
      np.random.seed(cls.random_seed)
      cls.model = cls.make_model()
      with cls.model:
          cls.step = cls.make_step()
          cls.trace = pm.sample(
              cls.n_samples,
              tune=cls.tune,
              step=cls.step,
              cores=cls.chains,
              return_inferencedata=False,
              compute_convergence_checks=False,
              random_seed=cls.random_seed,
          )
      cls.samples = {}
      for var in cls.model.unobserved_RVs:
          cls.samples[get_var_name(var)] = cls.trace.get_values(
              var, burn=cls.burn
          )
  
imports: import arviz
  import numpy
  import numpy.testing
  import pytensor.tensor
  from scipy import stats
  import pymc
  from pymc.backends.arviz import to_inference_data
  from pymc.util import get_var_name
label_desc: Use image node_id 1 for calling the BaseSampler obj's underlying member method code with example usage: obj.setup_class(cls) without return types