code: def _count_adap_avgpool(self, m, x, y):
      kernel = (
          torch.Tensor([*(x[0].shape[2:])])
          // torch.Tensor(list((m.output_size,))).squeeze()
      )
      total_add = int(torch.prod(kernel))
      total_div = 1
      kernel_ops = total_add + total_div
      num_elements = y[0].numel()
      total_ops = kernel_ops * num_elements
  
      return self._get_result(m, total_ops)
  
imports: import functools
  from collections import Counter
  from prettytable import PrettyTable
  import torch
  import torch.nn
  from torch.nn.utils.rnn import PackedSequence
  from nni.compression.base.wrapper import ModuleWrapper
label_desc: Use image node_id 9 for calling the ModelProfiler obj's underlying member method code with example usage: obj._count_adap_avgpool(m, x, y) and returns: self