code: def backward(self, indexes, grad_outputs):
      (x,) = self.get_retained_inputs()
      (x_hat,) = self.get_retained_outputs()
      (gx_hat,) = grad_outputs
      return _XHatGrad(
          self.eps,
          self.mean,
          self.inv_std,
          self.dummy_gamma,
          x_hat.array,
      ).apply((x, gx_hat))
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import configuration
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the _XHat obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: _XHatGrad