code: def forward(self, x):
      out = self.conv1(x)
      out = self.trans1(self.dense1(out))
      out = self.trans2(self.dense2(out))
      out = self.trans3(self.dense3(out))
      out = self.dense4(out)
      out = F.avg_pool2d(F.relu(self.bn(out)), 4)
      out = out.view(out.size(0), -1)
      out = self.linear(out)
      return out
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the DenseNet obj's underlying member method code with example usage: obj.forward(x) and returns: out