code: def __init__(
      self,
      outer_nc,
      inner_nc,
      submodule=None,
      outermost=False,
      innermost=False,
      use_dropout=False,
  ):
      super(UnetSkipConnectionBlock, self).__init__()
      self.outermost = outermost
      downconv = nn.Conv2D(
          inner_nc, kernel_size=4, strides=2, padding=1
      )
      downrelu = nn.LeakyReLU(0.2)
      downnorm = nn.InstanceNorm()
      uprelu = nn.Activation("relu")
      upnorm = nn.InstanceNorm()
      self.model = nn.HybridSequential()
      with self.model.name_scope():
          if outermost:
              self.model.add(downconv)
              if submodule is not None:
                  self.model.add(submodule)
              self.model.add(
                  uprelu,
                  nn.Conv2DTranspose(
                      outer_nc, kernel_size=4, strides=2, padding=1
                  ),
                  nn.Activation("tanh"),
              )
          elif innermost:
              self.model.add(
                  downrelu,
                  downconv,
                  uprelu,
                  nn.Conv2DTranspose(
                      outer_nc, kernel_size=4, strides=2, padding=1
                  ),
                  upnorm,
              )
          else:
              self.model.add(
                  downrelu,
                  downconv,
                  downnorm,
              )
              if submodule is not None:
                  self.model.add(submodule)
              self.model.add(
                  uprelu,
                  nn.Conv2DTranspose(
                      outer_nc, kernel_size=4, strides=2, padding=1
                  ),
                  upnorm,
              )
              if use_dropout:
                  self.model.add(nn.Dropout(0.5))
  
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 1 to create a new UnetSkipConnectionBlock object from inherited base classes: gluon.nn with example: obj = UnetSkipConnectionBlock(outer_nc, inner_nc, submodule, outermost, innermost, use_dropout)