code: def setUp(self):
      ndim = 0
      param_shape = (3,)
      self.gamma = cuda.cupy.random.uniform(0.5, 1, param_shape).astype(
          self.dtype
      )
      self.beta = cuda.cupy.random.uniform(-1, 1, param_shape).astype(
          self.dtype
      )
      shape = (7,) + param_shape + (2,) * ndim
      self.x = cuda.cupy.random.uniform(-1, 1, shape).astype(self.dtype)
      self.gy = cuda.cupy.random.uniform(-1, 1, shape).astype(
          self.dtype
      )
      self.args = [self.x, self.gamma, self.beta]
      head_ndim = self.gamma.ndim + 1
      self.aggr_axes = (0,) + tuple(
          six.moves.range(head_ndim, self.x.ndim)
      )
      self.mean = self.x.mean(axis=self.aggr_axes)
      self.var = self.x.var(axis=self.aggr_axes) + self.eps
      with chainer.using_config("use_cudnn", self.use_cudnn):
          self.expect = chainer.should_use_cudnn(">=auto", 5000)
  
imports: import unittest
  import warnings
  import numpy
  import six
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import backend
label_desc: Use image node_id 1 for calling the TestBatchNormalizationCudnnCall obj's underlying member method code with example usage: obj.setUp() without return types