code: def forward(self, input):
      logits_aux = None
      s0 = self.stem0(input)
      s1 = self.stem1(s0)
      for i, cell in enumerate(self.cells):
          s0, s1 = s1, cell(s0, s1, self.drop_path_prob)
          if i == 2 * self._layers // 3:
              if self._auxiliary and self.training:
                  logits_aux = self.auxiliary_head(s1)
      out = self.global_pooling(s1)
      logits = self.classifier(out.view(out.size(0), -1))
      return logits, logits_aux
  
imports: from operations import *
  from .utils import drop_path
label_desc: Use image node_id 2 for calling the NetworkImageNet obj's underlying member method code with example usage: obj.forward(input) and returns: logits,  logits_aux