code: def _maxpool2d_masked(
      prot: Pond,
      x: PondMaskedTensor,
      pool_size: Tuple[int, int],
      strides: Tuple[int, int],
      padding: str,
  ) -> PondPrivateTensor:
      with tf.name_scope("maxpool2d"):
          return prot.maxpool2d(
              x.unwrapped, pool_size, strides, padding
          )
  
imports: from __future__ import absolute_import
  import math
  import random
  import sys
  from typing import Optional
  from typing import Tuple
  import numpy
  import tensorflow
  from tf_encrypted.config import get_config
  from tf_encrypted.player import Player
  from tf_encrypted.protocol import memoize
  from tf_encrypted.protocol.pond import Pond
  from tf_encrypted.protocol.pond import PondMaskedTensor
  from tf_encrypted.protocol.pond import PondPrivateTensor
  from tf_encrypted.protocol.pond import PondPublicTensor
  from tf_encrypted.protocol.pond import PondTensor
  from tf_encrypted.protocol.pond import _type
  from tf_encrypted.protocol.protocol import nodes
  from tf_encrypted.protocol.securenn.odd_tensor import oddint64_factory
  from tf_encrypted.tensor import int64factory
  from tf_encrypted.tensor import native_factory
  from tf_encrypted.tensor.factory import AbstractFactory
  from tf_encrypted.tensor.factory import AbstractTensor
label_desc: Use image node_id 10 for calling a global function with example usage: _maxpool2d_masked(prot, x, pool_size, strides, padding) and returns: prot