code: def get_initial_cnn_pool():
      """Returns the initial pool for CNNs."""
      vgg_nets = [
          nn_examples.get_vgg_net(1),
          nn_examples.get_vgg_net(2),
          nn_examples.get_vgg_net(3),
          nn_examples.get_vgg_net(4),
      ]
      blocked_cnns = [
          nn_examples.get_blocked_cnn(3, 1, 1),  # 3
          nn_examples.get_blocked_cnn(3, 2, 1),  # 6
          nn_examples.get_blocked_cnn(3, 3, 1),  # 9
          nn_examples.get_blocked_cnn(3, 4, 1),  # 12
          nn_examples.get_blocked_cnn(3, 5, 1),  # 15
          nn_examples.get_blocked_cnn(4, 4, 1),  # 16
      ]
      resnet_cnns = []
      multidepth_cnns = []
      return vgg_nets + blocked_cnns + resnet_cnns + multidepth_cnns
  
file_path: dragonfly/dragonfly/nn/nn_opt_utils.py
imports: import numpy
  from .None import nn_examples
  from ..exd.experiment_caller import FunctionCaller
label_desc: Use image node_id 1 for calling a global function with example usage: get_initial_cnn_pool() and returns: unknown