class_docstr: Cross-channel normalization function used in AlexNet.
code: def forward_gpu(self, inputs):
      (x,) = inputs
      self.retain_inputs((0,))
      self.retain_outputs((0,))
  
      self.y = cuda.cupy.square(x)  # temporary
      self.scale = cuda.cupy.empty_like(self.y)
      _cu_conv_sum(self.scale, self.y, self.n)
      cuda.elementwise(
          "T x, T k, T alpha, T beta",
          "T y, T scale",
          """scale = k + alpha * scale;
                 y = x * pow(scale, -beta);""",
          "lrn_fwd",
      )(x, self.k, self.alpha, self.beta, self.y, self.scale)
      return (self.y,)
  
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 5 for calling the LocalResponseNormalization obj's underlying member method code with example usage: obj.forward_gpu(inputs) and returns: self