code: def pooling_layer(self, idx, inputs, size, stride, mode="init_model"):
      if self.disp_console and mode == "init_model":
          print(
              "Layer  %d : Type = Pool, Size = %d * %d, Stride = %d"
              % (idx, size, size, stride)
          )
  
      return tf.nn.max_pool(
          inputs,
          ksize=[1, size, size, 1],
          strides=[1, stride, stride, 1],
          padding="SAME",
          name=str(idx) + "_pool",
      )
  
imports: from __future__ import division
  from __future__ import print_function
  from builtins import str
  from builtins import range
  from past.utils import old_div
  from builtins import object
  import tensorflow
  import cv2
  import numpy
  import os
  import sys
  import argparse
  import pdb
  from tqdm import tqdm
label_desc: Use image node_id 11 for calling the YOLO_tiny_model_updated obj's underlying member method code with example usage: obj.pooling_layer(idx, inputs, size, stride, mode) and returns: tf