code: def forward_chainerx(self, inputs):
      # TODO(imanishi): Support it
      if any(d != 1 for d in self.dilate):
          return chainer.Fallback
      # TODO(imanishi): Support it
      if self.groups != 1:
          return chainer.Fallback
      # TODO(imanishi): Support it
      if any(a.dtype != inputs[0].dtype for a in inputs):
          return chainer.Fallback
      # TODO(imanishi): Supporft it
      if inputs[0].device.backend.name == "cuda" and self.ndim < 2:
          return chainer.Fallback
  
      stride = self.stride
      pad = self.pad
  
      return (chainerx.conv_transpose(*inputs, stride=stride, pad=pad),)
  
imports: import numpy
  from six import moves
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import configuration
  from chainer import function_node
  from chainer.functions.connection import convolution_2d
  from chainer.functions.connection import convolution_nd
  from chainer import utils
  from chainer.utils import conv
  from chainer.utils import conv_nd
  from chainer.utils import type_check
  import chainerx
label_desc: Use image node_id 8 for calling the DeconvolutionND obj's underlying member method code with example usage: obj.forward_chainerx(inputs) and returns: chainerx, chainer, chainer, chainer, chainer