code: def setUp_configure(self):
      from scipy import stats
  
      self.dist = distributions.Uniform
      self.scipy_dist = stats.uniform
  
      self.test_targets = set(
          [
              "batch_shape",
              "cdf",
              "entropy",
              "event_shape",
              "icdf",
              "log_prob",
              "mean",
              "sample",
              "stddev",
              "support",
              "variance",
          ]
      )
  
      if self.use_loc_scale:
          loc = numpy.random.uniform(-10, 0, self.shape).astype(
              numpy.float32
          )
          scale = numpy.random.uniform(0, 10, self.shape).astype(
              numpy.float32
          )
          self.params = {"loc": loc, "scale": scale}
          self.scipy_params = {"loc": loc, "scale": scale}
      else:
          low = numpy.random.uniform(-10, 0, self.shape).astype(
              numpy.float32
          )
          high = numpy.random.uniform(low, low + 10, self.shape).astype(
              numpy.float32
          )
          self.params = {"low": low, "high": high}
          self.scipy_params = {"loc": low, "scale": high - low}
  
      self.support = "[low, high]"
  
imports: import numpy
  from chainer import distributions
  from chainer import testing
label_desc: Use image node_id 1 for calling the TestUniform obj's underlying member method code with example usage: obj.setUp_configure() without return types