code: def forward(self, x):
      size = x.size()[2:]
      pool = self.gap(x)
      out = F.interpolate(
          pool, size, mode="bilinear", align_corners=True
      )
      return out
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.resnet import resnet18
label_desc: Use image node_id 2 for calling the _GlobalAvgPooling obj's underlying member method code with example usage: obj.forward(x) and returns: out