code: def __init__(self, in_ch):
      w = chainer.initializers.Normal(0.02)
      super(Encoder, self).__init__()
      with self.init_scope():
          self.c0 = L.Convolution2D(in_ch, 64, 3, 1, 1, initialW=w)
          self.c1 = ConvBNR(
              64,
              128,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c2 = ConvBNR(
              128,
              256,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c3 = ConvBNR(
              256,
              512,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c4 = ConvBNR(
              512,
              512,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c5 = ConvBNR(
              512,
              512,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c6 = ConvBNR(
              512,
              512,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
          self.c7 = ConvBNR(
              512,
              512,
              use_bn=True,
              sample="down",
              activation=F.leaky_relu,
              dropout=False,
          )
  
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 Encoder object from inherited base classes: chainer with example: obj = Encoder(in_ch)