code: def setUp_configure(self):
      from scipy import stats
  
      self.dist = lambda **params: distributions.Independent(
          distributions.Normal(**params), self.reinterpreted_batch_ndims
      )
  
      self.test_targets = set(
          [
              "batch_shape",
              "entropy",
              "event_shape",
              "log_prob",
              "support",
          ]
      )
  
      loc = utils.force_array(
          numpy.random.uniform(-1, 1, self.full_shape).astype(
              numpy.float32
          )
      )
      scale = utils.force_array(
          numpy.exp(
              numpy.random.uniform(-1, 1, self.full_shape)
          ).astype(numpy.float32)
      )
  
      if self.reinterpreted_batch_ndims is None:
          reinterpreted_batch_ndims = max(0, len(self.inner_shape) - 1)
      else:
          reinterpreted_batch_ndims = self.reinterpreted_batch_ndims
  
      batch_ndim = len(self.inner_shape) - reinterpreted_batch_ndims
      self.shape = self.inner_shape[:batch_ndim]
      self.event_shape = (
          self.inner_shape[batch_ndim:] + self.inner_event_shape
      )
      d = functools.reduce(operator.mul, self.event_shape, 1)
  
      if self.event_shape == ():
          self.scipy_dist = stats.norm
  
          self.params = {"loc": loc, "scale": scale}
          self.scipy_params = {"loc": loc, "scale": scale}
  
      else:
          self.scipy_dist = stats.multivariate_normal
  
          scale_tril = (
              numpy.eye(d).astype(numpy.float32)
              * scale.reshape(self.shape + (d,))[..., None]
          )
          cov = numpy.einsum(
              "...ij,...jk->...ik", scale_tril, scale_tril
          )
  
          self.params = {"loc": loc, "scale": scale}
          self.scipy_params = {
              "mean": numpy.reshape(loc, self.shape + (d,)),
              "cov": cov,
          }
  
imports: import functools
  import itertools
  import operator
  import numpy
  from chainer import distributions
  from chainer import testing
  from chainer.testing import array
  from chainer.testing import attr
  from chainer import utils
label_desc: Use image node_id 2 for calling the TestIndependentNormal obj's underlying member method code with example usage: obj.setUp_configure() without return types