code: def __init__(self, in_size, ch):
      super(BottleNeckB, self).__init__()
      initialW = initializers.HeNormal()
  
      with self.init_scope():
          self.conv1 = L.Convolution2D(
              in_size, ch, 1, 1, 0, initialW=initialW, nobias=True
          )
          self.bn1 = L.BatchNormalization(ch)
          self.conv2 = L.Convolution2D(
              ch, ch, 3, 1, 1, initialW=initialW, nobias=True
          )
          self.bn2 = L.BatchNormalization(ch)
          self.conv3 = L.Convolution2D(
              ch, in_size, 1, 1, 0, initialW=initialW, nobias=True
          )
          self.bn3 = L.BatchNormalization(in_size)
  
imports: import chainer
  import chainer.functions
  from chainer import initializers
  import chainer.links
label_desc: Use image node_id 1 to create a new BottleNeckB object from inherited base classes: chainer with example: obj = BottleNeckB(in_size, ch)