code: def __init__(
      self,
      path,
      entropy_penalty,
      encoder: EncoderNet,
      wider_actor: WiderActorNet,
      deeper_actor: DeeperActorNet,
      opt_config,
  ):
      BaseController.__init__(self, path)
      self.entropy_penalty = entropy_penalty
  
      self.encoder = encoder
      self.wider_actor = wider_actor
      self.deeper_actor = deeper_actor
      self.opt_config = opt_config
  
      self.graph = tf.Graph()
      self.obj, self.train_step = None, None
      with self.graph.as_default():
          self._define_input()
          self.build_forward()
          self.build_training_process()
          self.global_variables_initializer = (
              tf.global_variables_initializer()
          )
          self.saver = tf.train.Saver()
      self._initialize_session()
  
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 3 to create a new RLNet2NetController object from inherited base classes: BaseController with example: obj = RLNet2NetController(path, entropy_penalty, encoder, wider_actor, deeper_actor, opt_config)