code: def build_forward(self):
      encoder_output, encoder_state = self.encoder.build()
      feed2wider_output = encoder_output[: self.wider_seg_deeper]
      feed2deeper_output = encoder_output[self.wider_seg_deeper :]
      if isinstance(encoder_state, tf.contrib.rnn.LSTMStateTuple):
          encoder_state_c = encoder_state.c
          encoder_state_h = encoder_state.h
  
          feed2wider_c = encoder_state_c[: self.wider_seg_deeper]
          feed2wider_h = encoder_state_h[: self.wider_seg_deeper]
          feed2wider_state = tf.contrib.rnn.LSTMStateTuple(
              c=feed2wider_c, h=feed2wider_h
          )
  
          feed2deeper_c = encoder_state_c[self.wider_seg_deeper :]
          feed2deeper_h = encoder_state_h[self.wider_seg_deeper :]
          feed2deeper_state = tf.contrib.rnn.LSTMStateTuple(
              c=feed2deeper_c, h=feed2deeper_h
          )
      elif isinstance(encoder_state, tf.Tensor):
          feed2wider_state = encoder_state[: self.wider_seg_deeper]
          feed2deeper_state = encoder_state[self.wider_seg_deeper :]
      else:
          raise ValueError
  
      self.wider_actor.build_forward(feed2wider_output)
      self.deeper_actor.build_forward(
          feed2deeper_output,
          feed2deeper_state,
          self.is_training,
          self.deeper_decision_trajectory,
      )
  
imports: from ..meta_controller.base_controller import WiderActorNet, DeeperActorNet, EncoderNet, BaseController
  import tensorflow
  import os
  from tensorflow.python.ops import array_ops
  from ..models.basic_model import BasicModel
  import shutil
  import numpy
label_desc: Use image node_id 6 for calling the RLNet2NetController obj's underlying member method code with example usage: obj.build_forward() without return types