code: def backward(self, indexes, grad_outputs):
      inputs = self.get_retained_inputs()
      gW = EmbedIDGrad(self._w_shape, self.ignore_label).apply(
          inputs + grad_outputs
      )[0]
      return None, gW
  
imports: import numpy
  import six
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the EmbedIDFunction obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: None,  gW