code: def forward_cpu(self, inputs):
      self.retain_inputs((0, 1))
      x, gy = inputs
  
      if self.groups > 1:
          return self._forward_grouped_convolution(x, gy)
      else:
          return self._forward_cpu_core(x, gy)
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import configuration
  from chainer import function_node
  import chainer.functions
  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 3 for calling the Convolution2DGradW obj's underlying member method code with example usage: obj.forward_cpu(inputs) and returns: self, self