code: def main():
      parser = argparse.ArgumentParser(
          description="Evaluating convnet from ILSVRC2012 dataset"
      )
      parser.add_argument(
          "val", help="Path to root of the validation dataset"
      )
      parser.add_argument("--model", choices=sorted(models.keys()))
      parser.add_argument("--pretrained-model")
      parser.add_argument("--dataset", choices=("imagenet",))
      parser.add_argument("--gpu", type=int, default=-1)
      parser.add_argument("--batchsize", type=int)
      parser.add_argument("--crop", choices=("center", "10"))
      parser.add_argument("--resnet-arch")
      args = parser.parse_args()
  
      dataset, eval_, model, batchsize = setup(
          args.dataset,
          args.model,
          args.pretrained_model,
          args.batchsize,
          args.val,
          args.crop,
          args.resnet_arch,
      )
  
      if args.gpu >= 0:
          chainer.cuda.get_device(args.gpu).use()
          model.to_gpu()
  
      iterator = iterators.MultiprocessIterator(
          dataset,
          batchsize,
          repeat=False,
          shuffle=False,
          n_processes=6,
          shared_mem=300000000,
      )
  
      print("Model has been prepared. Evaluation starts.")
      in_values, out_values, rest_values = apply_to_iterator(
          model.predict, iterator, hook=ProgressHook(len(dataset))
      )
      del in_values
  
      eval_(out_values, rest_values)
  
imports: import argparse
  import numpy
  import chainer
  import chainer.functions
  from chainer import iterators
  from chainercv.datasets import directory_parsing_label_names
  from chainercv.datasets import DirectoryParsingLabelDataset
  from chainercv.links import FeaturePredictor
  from chainercv.links import MobileNetV2
  from chainercv.links import ResNet101
  from chainercv.links import ResNet152
  from chainercv.links import ResNet50
  from chainercv.links import SEResNet101
  from chainercv.links import SEResNet152
  from chainercv.links import SEResNet50
  from chainercv.links import SEResNeXt101
  from chainercv.links import SEResNeXt50
  from chainercv.links import VGG16
  from chainercv.utils import apply_to_iterator
  from chainercv.utils import ProgressHook
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types