code: def max_pool(_input, k=2, s=2):
      ksize = [1, k, k, 1]
      strides = [1, s, s, 1]
      padding = "VALID"
      # if stride = 1, keep the image size unchanged
      if s == 1:
          padding = "SAME"
      output = tf.nn.max_pool(_input, ksize, strides, padding)
      return output
  
imports: import os
  import shutil
  import tensorflow
  import numpy
  import time
  from datetime import timedelta
  import json
  import pickle
label_desc: Use image node_id 20 for calling the BasicModel obj's underlying member method code with example usage: obj.max_pool(_input, k, s) and returns: output