code: def setUp_configure(self):
      from scipy import stats
  
      self.dist = distributions.Bernoulli
      self.scipy_dist = stats.bernoulli
      self.options = {"binary_check": self.binary_check}
  
      self.test_targets = set(
          [
              "batch_shape",
              "entropy",
              "log_prob",
              "mean",
              "prob",
              "sample",
              "stddev",
              "support",
              "variance",
          ]
      )
  
      if self.extreme_values:
          p = numpy.random.randint(0, 2, self.shape).astype(
              numpy.float32
          )
      else:
          p = numpy.random.uniform(0, 1, self.shape).astype(
              numpy.float32
          )
  
      self.params = {"p": p}
      self.scipy_params = {"p": p}
  
      self.support = "{0, 1}"
      self.continuous = False
  
      self.old_settings = None
      if self.extreme_values:
          self.old_settings = numpy.seterr(
              divide="ignore", invalid="ignore"
          )
  
imports: import unittest
  import numpy
  from chainer import backend
  from chainer.backends import cuda
  from chainer import distributions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 1 for calling the TestBernoulli obj's underlying member method code with example usage: obj.setUp_configure() without return types