class_docstr: Multi-Layer Perceptron
code: def __call__(self, x):
      h = x
      if self.hidden_sizes:
          for link in self.hidden_layers:
              h = self.nonlinearity(link(h))
      return self.output(h)
  
file_path: chainerrl/chainerrl/links/mlp.py
imports: import chainer
  from chainer import functions
  from chainer.initializers import LeCunNormal
  from chainer import links
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.__call__(x) and returns: self