code: def forward(self, x):
      f1 = self.feat_1(x)
      f2 = self.feat_2(f1)
      f3 = self.feat_3(f2)
      f4 = self.feat_4(f3)
      return f4, f3
  
imports: from collections import OrderedDict
  import math
  import re
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils import model_zoo
  from torchvision.models.densenet import DenseNet
  from torchvision.models.squeezenet import squeezenet1_1
label_desc: Use image node_id 2 for calling the SqueezeNet obj's underlying member method code with example usage: obj.forward(x) and returns: f4,  f3