code: def logits(self, features):
      adaptiveAvgPoolWidth = features.shape[2]
      x = F.avg_pool2d(features, kernel_size=adaptiveAvgPoolWidth)
      x = x.view(x.size(0), -1)
      x = self.last_linear(x)
      return x
  
imports: import torch.nn
  import torch.nn.functional
  import math
  import torch.utils.model_zoo
label_desc: Use image node_id 4 for calling the FBResNet obj's underlying member method code with example usage: obj.logits(features) and returns: x