code: def forward_gpu(self, inputs):
      x, y, gy = inputs
      summand = cuda.elementwise(
          "T scale, T y, T gy",
          "T summand",
          "summand = y * gy / scale",
          "lrn_bwd_summand",
      )(self.scale, y, gy)
      gx = cuda.cupy.empty_like(x)
      _cu_conv_sum(gx, summand, self.n)
      cuda.elementwise(
          " T x, T gy, T scale, T beta, T coeff",
          "T gx",
          "gx = pow(scale, -beta) * gy - coeff * x * gx",
          "lrn_bwd",
      )(x, gy, self.scale, self.beta, 2 * self.alpha * self.beta, gx)
      return (gx,)
  
imports: import numpy
  import six
  from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the LocalResponseNormalizationGrad obj's underlying member method code with example usage: obj.forward_gpu(inputs) and returns: gx