code: def _forward_cpu_core(self, x, W, b):
      if self._use_ideep:
          return self._forward_ideep(x, W, b)
  
      gcol = numpy.tensordot(W, x, (0, 1)).astype(x.dtype, copy=False)
      gcol = numpy.rollaxis(gcol, 3)
      y = conv.col2im_cpu(
          gcol,
          self.sy,
          self.sx,
          self.ph,
          self.pw,
          self.outh,
          self.outw,
          dy=self.dy,
          dx=self.dx,
      )
      # b, k, h, w
      if b is not None:
          y += b.reshape((1, b.size, 1, 1))
      return (y,)
  
imports: import numpy
  import chainer
  from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import configuration
  from chainer import function_node
  import chainer.functions
  from chainer.functions.connection import convolution_2d
  from chainer import memory_layouts
  from chainer.utils import argument
  from chainer.utils import conv
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 6 for calling the Deconvolution2DFunction obj's underlying member method code with example usage: obj._forward_cpu_core(x, W, b) and returns: y, self