code: def forward(self, x):
      x = self.features(x)
      x = self.classifier(x)
      return x.view([int(x.size(0)), self.num_classes])
  
imports: import keras
  import sys
  import numpy
  import math
  import torch
  import torchvision
  import torch.nn
  from torch.autograd import Variable
  from pytorch2keras.converter import pytorch_to_keras
  import math
  import torch
  import torch.nn
  import torch.nn.init
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: x