class_docstr: Global Weighted Average Pooling from paper "Global Weighted Average
  Pooling Bridges Pixel-level Localization and Image-level Classification"
code: def norm(self, x: torch.Tensor):
      return x / x.sum(dim=[2, 3], keepdim=True)
  
imports: from typing import Union, Dict
  import torch
  import torch.nn.functional
  from torch.nn.modules.module import _IncompatibleKeys
  from torch import Tensor, nn
label_desc: Use image node_id 3 for calling the GlobalWeightedAvgPool2d obj's underlying member method code with example usage: obj.norm(x) and returns: unknown