docstr: Current forward_expected implementation depends on
  F.deconvolution_2d itself and thus it's only capable
  of checking consistency between backends, not absolute
  correctness of computations
docstr_tok: ["Current","forward_expected","implementation","depends","on","F.deconvolution_2d","itself","and","thus","it","'s","only","capable","of","checking","consistency","between","backends",",","not","absolute","correctness","of","computations"]
code: def forward_expected(self, inputs):
      """
      Current forward_expected implementation depends on
      F.deconvolution_2d itself and thus it's only capable
      of checking consistency between backends, not absolute
      correctness of computations
      """
      if self.nobias:
          x, W = inputs
          b = None
      else:
          x, W, b = inputs
      y_expected = F.deconvolution_2d(
          x,
          W,
          b,
          stride=self.stride,
          pad=self.pad,
          outsize=self.outsize,
          dilate=self.dilate,
          groups=self.groups,
      )
      return (y_expected.array,)
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainer import testing
  from chainer.testing import array
  from chainer.testing import attr
  from chainer.testing import parameterize
  from chainer.utils import conv
label_desc: Use image node_id 4 for calling the TestDeconvolution2DFunction obj's underlying member method code with example usage: obj.forward_expected(inputs) and returns: y_expected