code: def __init__(
      self,
      n,
      k,
      alpha,
      beta,
      use_ideep,
      scale=None,
      indexes=None,
      unit_scale=None,
  ):
      self.n = n
      self.k = k
      self.alpha = alpha
      self.beta = beta
      self._use_ideep = use_ideep
  
      self.scale = scale
      self.indexes = indexes
      self.unit_scale = unit_scale
  
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 1 to create a new LocalResponseNormalizationGrad object from inherited base classes: function_node with example: obj = LocalResponseNormalizationGrad(n, k, alpha, beta, use_ideep, scale, indexes, unit_scale)