code: def __init__(self, n_vocab, n_units, n_label):
      super(ThinStackRecursiveNet, self).__init__(
          embed=L.EmbedID(n_vocab, n_units),
          l=L.Linear(n_units * 2, n_units),
          w=L.Linear(n_units, n_label),
      )
      self.n_units = n_units
  
imports: import argparse
  import warnings
  import numpy
  import chainer
  import chainer.functions
  import chainer.links
  from chainer import reporter
  from chainer import training
  from chainer.training import extensions
  import data
  import thin_stack
label_desc: Use image node_id 1 to create a new ThinStackRecursiveNet object from inherited base classes: chainer with example: obj = ThinStackRecursiveNet(n_vocab, n_units, n_label)