class_docstr: Linear layer with BatchNormalization.
code: def __init__(self, in_size, out_size):
      super().__init__()
      with self.init_scope():
          self.linear = L.Linear(in_size, out_size)
          bn = L.BatchNormalization(out_size)
          bn.avg_var[:] = 1
          self.bn = bn
  
file_path: chainerrl/chainerrl/links/mlp_bn.py
imports: import chainer
  from chainer import functions
  from chainer.initializers import LeCunNormal
  from chainer import links
label_desc: Use image node_id 1 to create a new LinearBN object from inherited base classes: chainer with example: obj = LinearBN(in_size, out_size)