code: def _networks(proto, default_context, batch_size, network_names=None):
      # Load networks
      networks = OrderedDict()
      all_variables = {}
  
      # Random generator for using the same init parameters in all devices
      rng = numpy.random.RandomState(0)
  
      for np in proto.network:
          if not network_names or np.name in network_names:
              networks[np.name] = _network(
                  np, default_context, batch_size, all_variables, rng
              )
  
      return networks
  
imports: from collections import OrderedDict
  import google.protobuf.text_format
  import itertools
  import numpy
  import os
  import re
  import shutil
  import tempfile
  from nnabla.initializer import NormalInitializer, UniformInitializer, ConstantInitializer, RangeInitializer, calc_normal_std_he_forward, calc_normal_std_he_backward, calc_normal_std_glorot, calc_uniform_lim_glorot
  from nnabla.logger import logger
  from nnabla.parameter import get_parameter_or_create
  from nnabla.utils import nnabla_pb2
  from nnabla.utils.data_iterator import data_iterator_csv_dataset, data_iterator_cache
  from nnabla.utils.create_cache import CreateCache
  from nnabla.utils.load_function import _create_function_instance
  from nnabla.utils.nnp_format import nnp_version
  from nnabla.utils.communicator_util import current_communicator, single_or_rankzero
  from nnabla.utils.learning_rate_scheduler import PolynomialScheduler, CosineScheduler, ExponentialScheduler, StepScheduler, LinearWarmupScheduler
  from legacy_network import Network
  from nnabla.utils.progress import progress
  from legacy_get_file_handle import get_file_handle_load, get_buf_type
  import nnabla
  import nnabla.function
  import nnabla.solver
label_desc: Use image node_id 14 for calling a global function with example usage: _networks(proto, default_context, batch_size, network_names) and returns: networks