code: def forward(self, x):  # skipcq: PYL-W0221
      x = F.adaptive_avg_pool2d(x, output_size=1)
      if self.flatten:
          x = x.view(x.size(0), x.size(1))
      return x
  
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 2 for calling the GlobalAvgPool2d obj's underlying member method code with example usage: obj.forward(x) and returns: x