code: def backward(self, indexes, grad_outputs):
      y, gy = self.get_retained_inputs()
      ggx = grad_outputs[0]
  
      y_mul_ggx = y * ggx
      grad_y = -2 * gy * y_mul_ggx
      ggy = ggx - y * y_mul_ggx
      return grad_y, ggy
  
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
  import chainerx
label_desc: Use image node_id 4 for calling the TanhGrad obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: grad_y,  ggy