code: def define_D(ndf, which_model_netD, n_layers_D=3, use_sigmoid=False):
      if which_model_netD == "basic":
          netD = NLayerDiscriminator(
              ndf, n_layers=3, use_sigmoid=use_sigmoid
          )
      elif which_model_netD == "n_layers":
          netD = NLayerDiscriminator(
              ndf, n_layers_D, use_sigmoid=use_sigmoid
          )
      else:
          raise NotImplementedError(
              "Discriminator model name [%s] is not recognized"
              % which_model_netD
          )
  
      return netD
  
imports: import argparse
  import random
  from mxnet import gluon, image, autograd
  from mxnet.gluon.data.vision import transforms
  from mxnet.base import numeric_types
  import gluoncv
  from gluoncv import utils
  from mxnet.gluon.data import DataLoader
  from mxnet.gluon import nn
  import mxnet.ndarray
  import mxnet
  import os
  import numpy
  from mxboard import SummaryWriter
label_desc: Use image node_id 2 for calling a global function with example usage: define_D(ndf, which_model_netD, n_layers_D, use_sigmoid) and returns: netD