code: def backward(self, indexes, grad_outputs):
      x, beta = self.get_retained_inputs()
      (gy,) = grad_outputs
  
      shape = _get_extended_shape(beta, x)
      reduction_axes = _get_reduction_axes(beta, x)
  
      return SwishGrad(shape, reduction_axes).apply((x, beta, gy))
  
imports: import numpy
  import chainer
  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 Swish obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: SwishGrad