code: def rename_LRN(self, source_node):
      IR_node = self.IR_graph.node.add()
  
      # name, op
      PaddleParser._copy_and_reop(source_node, IR_node, "LRN")
  
      # input edge
      self.convert_inedge(source_node, IR_node)
  
      # layer and spec
      lrn_spec = source_node.layer
      spec = lrn_spec.inputs[0].norm_conf
      channels = spec.channels
      size = spec.size
      alpha = spec.scale
      beta = spec.pow
      img_size_x = spec.img_size
      img_size_y = (
          spec.img_size_y if spec.HasField("img_size_y") else img_size_x
      )
      output_x = spec.output_x
      output_y = (
          spec.output_y if spec.HasField("output_y") else output_x
      )
  
      # output shape
      output_shapes = [-1, output_y, output_x, channels]
      self.shape_dict[source_node.name] = output_shapes
      PaddleParser._set_output_shape(
          source_node, IR_node, output_shapes
      )
  
      # alpha
      IR_node.attr["alpha"].f = alpha * size
      # beta
      IR_node.attr["beta"].f = beta
      # nsize
      IR_node.attr["size"].i = int(size)
  
      if (
          lrn_spec.HasField("active_type")
          and lrn_spec.active_type != ""
      ):
          IR_node_act = self._defuse_activation(source_node)
          PaddleParser._set_output_shape(
              source_node, IR_node_act, output_shapes
          )
  
imports: from __future__ import absolute_import
  import os
  import gzip
  from six import string_types
  import paddle.v2
  import paddle.trainer_config_helpers.layers
  import numpy
  from mmdnn.conversion.paddle.paddle_graph import PaddleGraph
  import mmdnn.conversion.common.IR.graph_pb2
  from mmdnn.conversion.common.IR.graph_pb2 import NodeDef, GraphDef, DataType
  from mmdnn.conversion.common.DataStructure.parser import Parser
  from mmdnn.conversion.common.utils import *
label_desc: Use image node_id 18 for calling the PaddleParser obj's underlying member method code with example usage: obj.rename_LRN(source_node) without return types