code: def get_configurations(netG, netD):
      
      # loss
      loss = gluon.loss.SoftmaxCrossEntropyLoss()
  
      # initialize the generator and the discriminator
      netG.initialize(mx.init.Normal(0.02), ctx=ctx)
      netD.initialize(mx.init.Normal(0.02), ctx=ctx)
  
      # trainer for the generator and the discriminator
      trainerG = gluon.Trainer(netG.collect_params(), 'adam', {'learning_rate': opt.lr, 'beta1': opt.beta1})
      trainerD = gluon.Trainer(netD.collect_params(), 'adam', {'learning_rate': opt.lr, 'beta1': opt.beta1})
  
      return loss, trainerG, trainerD
docs: Get configurations for net