code: def setUp(self):
      self.N = 2
      self.out_channels = 2
      self.ndim = len(self.dims)
      self.ksize = (3,) * self.ndim
      self.stride = (2,) * self.ndim
      self.pad = (1,) * self.ndim
      if self.nobias:
          self.param_names = ("W",)
      else:
          self.param_names = ("W", "b")
  
      if self.used_outsize == "case1" or self.used_outsize == "None":
          # Use output size determined with get_deconv_outsize.
          outs = tuple(
              conv.get_deconv_outsize(d, k, s, p)
              for (d, k, s, p) in zip(
                  self.dims, self.ksize, self.stride, self.pad
              )
          )
      elif self.used_outsize == "case2":
          # Use possible output size other than the one determined with
          # get_deconv_outsize.
          outs = tuple(
              conv.get_deconv_outsize(d, k, s, p) + 1
              for (d, k, s, p) in zip(
                  self.dims, self.ksize, self.stride, self.pad
              )
          )
      if self.used_outsize != "None":
          self.outsize = outs
      else:
          self.outsize = None
  
      self.x_shape = (self.N, 4) + self.dims
  
      self.check_backward_options.update(
          {"eps": 1e-2, "atol": 1e-4, "rtol": 1e-3}
      )
      if self.dtype == numpy.float16:
          self.check_forward_options.update(
              {"atol": 5e-3, "rtol": 5e-2}
          )
          self.check_backward_options.update(
              {"eps": 2**-3, "atol": 1e-2, "rtol": 1e-1}
          )
  
imports: import unittest
  import numpy
  from chainer.backends import cuda
  import chainer.functions
  from chainer import initializers
  from chainer.links.connection import deconvolution_nd
  from chainer import testing
  from chainer.testing import parameterize
  from chainer.utils import conv
label_desc: Use image node_id 1 for calling the TestDeconvolutionND obj's underlying member method code with example usage: obj.setUp() without return types