class_docstr: A BOW encoder with word embedding and MLP.
  
  This model encodes a sentence as just a set of words by averaging.
  Additionally, its output is fed into a multilayer perceptron.
  
  Args:
      n_layers (int): The number of layers of MLP.
      n_vocab (int): The size of vocabulary.
      n_units (int): The number of units of MLP and word embedding.
      dropout (float): The dropout ratio.
code: def forward(self, xs):
      h = self.bow_encoder(xs)
      h = self.mlp_encoder(h)
      return h
  
imports: import numpy
  import chainer
  import chainer.functions
  import chainer.links
  from chainer import reporter
label_desc: Use image node_id 2 for calling the BOWMLPEncoder obj's underlying member method code with example usage: obj.forward(xs) and returns: h