code: def forward(self, x):
      s0 = s1 = self.stem(x)
  
      aux_logits = None
      for i, cell in enumerate(self.cells):
          s0, s1 = s1, cell(s0, s1)
          if i == self.aux_pos and self.training:
              aux_logits = self.aux_head(s1)
  
      out = self.gap(s1)
      out = out.view(out.size(0), -1)  # flatten
      logits = self.linear(out)
  
      if aux_logits is not None:
          return logits, aux_logits
      return logits
  
imports: from collections import OrderedDict
  import torch
  import torch.nn
  import ops
  from nni.retiarii.nn.pytorch import LayerChoice, InputChoice
label_desc: Use image node_id 2 for calling the CNN obj's underlying member method code with example usage: obj.forward(x) and returns: logits, logits,  aux_logits