code: def __call__(self, obs, batched=False):
      out = self.network(obs, batched)
      W, b = dy.parameter(self.W), dy.parameter(self.b)
      As = dy.affine_transform([b, W, out])
      if self.dueling:
          W_extra, b_extra = dy.parameter(self.W_extra), dy.parameter(
              self.b_extra
          )
          V = dy.affine_transform([b_extra, W_extra, out])
          return As, V
      return As
  
file_path: dynet/examples/reinforcement-learning/network.py
imports: import dynet
label_desc: Use image node_id 2 for calling the Header obj's underlying member method code with example usage: obj.__call__(obs, batched) and returns: As, As,  V