code: def loss_dis(self, dis, y_fake, y_real):
      batchsize = len(y_fake)
      L1 = F.sum(F.softplus(-y_real)) / batchsize
      L2 = F.sum(F.softplus(y_fake)) / batchsize
      loss = L1 + L2
      chainer.report({"loss": loss}, dis)
      return loss
  
file_path: chainer/examples/dcgan/updater.py
imports: import chainer
  import chainer.functions
  from chainer import Variable
label_desc: Use image node_id 2 for calling the DCGANUpdater obj's underlying member method code with example usage: obj.loss_dis(dis, y_fake, y_real) and returns: loss