code: def rename_Pooling(self, source_node):
      IR_node = self._convert_identity_operation(
          source_node, new_op="Pool"
      )
      kwargs = {}
      if source_node.get_attr("pool") == "MAX":
          kernel = source_node.get_attr("kernel_size")
          kwargs["kernel_shape"] = [1, kernel, kernel, 1]
          stride = source_node.get_attr("stride")
          kwargs["strides"] = [1, stride, stride, 1]
          kwargs["pooling_type"] = source_node.get_attr("pool")
          pad = source_node.get_attr("padding")
          IR_node.attr["pads"].list.i.extend(
              ([0] + [pad, pad] + [0]) * 2
          )
  
      # for image classification(resnet) AVG pooling
      else:
          print(source_node.layer)
          innode = self.dk_graph.get_node(source_node.in_edges[0])
          input_shape = innode.get_attr("_output_shape")
          kwargs["kernel_shape"] = [1] + input_shape[1:2] + [1]
          kwargs["strides"] = [1, 1, 1, 1]
  
          kwargs["pooling_type"] = source_node.get_attr("pool")
          IR_node.attr["pads"].list.i.extend(([0, 0, 0, 0]) * 2)
  
      assign_IRnode_values(IR_node, kwargs)
  
imports: import os
  import numpy
  from mmdnn.conversion.common.utils import *
  from mmdnn.conversion.darknet.prototxt import *
  from mmdnn.conversion.darknet.darknet_utils import *
  from mmdnn.conversion.darknet.darknet_graph import DarknetGraph
  import mmdnn.conversion.common.IR.graph_pb2
  from mmdnn.conversion.common.DataStructure.parser import Parser
  from mmdnn.conversion.common.IR.graph_pb2 import NodeDef, GraphDef, DataType
label_desc: Use image node_id 13 for calling the DarknetParser obj's underlying member method code with example usage: obj.rename_Pooling(source_node) without return types