code: def get_block_layer_num(net_configs):
      if len(net_configs) == 1:
          net_config = net_configs[0]
          block_layer_num = []
          _count = 0
          for layer in net_config.layer_cascade.layers[:-1]:
              if isinstance(layer, PoolLayer):
                  block_layer_num.append(_count)
                  _count = 0
              else:
                  _count += 1
          block_layer_num.append(_count)
          return np.array([block_layer_num])
      else:
          block_layer_num = []
          for net_config in net_configs:
              block_layer_num.append(get_block_layer_num([net_config]))
          return np.concatenate(block_layer_num, axis=0)
  
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 3 for calling a global function with example usage: get_block_layer_num(net_configs) and returns: np, np