code: def sample_wider_decision(self, input_seq, seq_len):
      batch_size = len(seq_len)
      wider_decision, wider_probs = self.sess.run(
          fetches=[self.wider_actor.decision, self.wider_actor.probs],
          feed_dict={
              self.encoder.input_seq: input_seq,
              self.encoder.seq_len: seq_len,
              self.wider_seg_deeper: batch_size,
          },
      )  # [batch_size, num_steps]
      return wider_decision, wider_probs
  
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 8 for calling the RLNet2NetController obj's underlying member method code with example usage: obj.sample_wider_decision(input_seq, seq_len) and returns: wider_decision,  wider_probs