code: def __init__(self, out_ch):
      w = chainer.initializers.Normal(0.02)
      super(Decoder, self).__init__()
      with self.init_scope():
          self.c0 = ConvBNR(
              512,
              512,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=True,
          )
          self.c1 = ConvBNR(
              1024,
              512,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=True,
          )
          self.c2 = ConvBNR(
              1024,
              512,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=True,
          )
          self.c3 = ConvBNR(
              1024,
              512,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=False,
          )
          self.c4 = ConvBNR(
              1024,
              256,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=False,
          )
          self.c5 = ConvBNR(
              512,
              128,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=False,
          )
          self.c6 = ConvBNR(
              256,
              64,
              use_bn=True,
              sample="up",
              activation=F.relu,
              dropout=False,
          )
          self.c7 = L.Convolution2D(128, out_ch, 3, 1, 1, initialW=w)
  
imports: from __future__ import print_function
  import chainer
  import chainer.functions
  import chainer.links
label_desc: Use image node_id 1 to create a new Decoder object from inherited base classes: chainer with example: obj = Decoder(out_ch)