code: def forward(self, x):
      features = self.features(x)
      out = F.relu(features, True)
      out = F.adaptive_avg_pool2d(out, (1, 1)).view(
          features.size(0), -1
      )
      out = self.classifier(out)
      return out
  
imports: import re
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
  from collections import OrderedDict
label_desc: Use image node_id 2 for calling the DenseNet obj's underlying member method code with example usage: obj.forward(x) and returns: out