code: def get_net_seq(net_configs, vocabulary, num_steps):
      net_str_list = get_net_str(net_configs)
      net_seq = []
      seq_len = []
      for net_str in net_str_list:
          net_str = re.split("_", net_str)
          net_code = vocabulary.get_code(net_str)
          _len = len(net_code)
          net_code += [
              vocabulary.pad_code
              for _ in range(len(net_code), num_steps)
          ]
          net_seq.append(net_code)
          seq_len.append(_len)
      return np.array(net_seq), np.array(seq_len)
  
file_path: auptimizer/src/aup/Proposer/eas/arch_search/arch_search_convnet_net2net.py
imports: from ..expdir_monitor.arch_manager import ArchManager
  from ..meta_controller.base_controller import Vocabulary, EncoderNet, WiderActorNet, DeeperActorNet
  from ..meta_controller.rl_controller import ReinforceNet2NetController
  from time import gmtime, strftime, time
  from datetime import timedelta
  from ..models.layers import ConvLayer, FCLayer, PoolLayer
  import re
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: get_net_seq(net_configs, vocabulary, num_steps) and returns: np,  np