code: def DiscriminatorLayerLoss():
      '''Calculate the discriminator layer loss
      '''
  
      data = mx.sym.Variable('data')
  
      label = mx.sym.Variable('label')
  
      data = mx.sym.Flatten(data)
      label = mx.sym.Flatten(label)
  
      label = mx.sym.BlockGrad(label)
  
      zeros = mx.sym.zeros_like(data)
  
      output = -GaussianLogDensity(label, data, zeros)
  
      dloss = mx.symbol.MakeLoss(mx.symbol.mean(output),name='lloss')
  
      return dlosf DiscriminatorLayerLoss():
      '''Calculate the discriminator layer loss
      '''
  
      data = mx.sym.Variable('data')
  
      label = mx.sym.Variable('label')
  
      data = mx.sym.Flatten(data)
      label = mx.sym.Flatten(label)
  
      label = mx.sym.BlockGrad(label)
  
      zeros = mx.sym.zeros_like(data)
  
      output = -GaussianLogDensity(label, data, zeros)
  
      dloss = mx.symbol.MakeLoss(mx.symbol.mean(output),name='lloss')
  
      return dloss
docs: Calculate the discriminator layer loss