class_docstr: YOLOv3.
  
  This is a model of YOLOv3 [#]_.
  This model uses :class:`~chainercv.links.model.yolo.Darknet53Extractor` as
  its feature extractor.
  
  .. [#] Joseph Redmon, Ali Farhadi.
     YOLOv3: An Incremental Improvement. arXiv 2018.
  
  Args:
     n_fg_class (int): The number of classes excluding the background.
     pretrained_model (string): The weight file to be loaded.
         This can take :obj:`'voc0712'`, `filepath` or :obj:`None`.
         The default value is :obj:`None`.
  
          * :obj:`'voc0712'`: Load weights trained on trainval split of                 PASCAL VOC 2007 and 2012.                 The weight file is downloaded and cached automatically.                 :obj:`n_fg_class` must be :obj:`20` or :obj:`None`.                 These weights were converted from the darknet model.                 The conversion code is                 `chainercv/examples/yolo/darknet2npz.py`.
          * `filepath`: A path of npz file. In this case, :obj:`n_fg_class`                 must be specified properly.
          * :obj:`None`: Do not load weights.
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code: def to_cpu(self):
      super(YOLOv3, self).to_cpu()
      self._default_bbox = cuda.to_cpu(self._default_bbox)
      self._step = cuda.to_cpu(self._step)
  
imports: from __future__ import division
  import itertools
  import numpy
  import chainer
  from chainer.backends import cuda
  import chainer.functions
  from chainer.links import Convolution2D
  from chainercv.links import Conv2DBNActiv
  from chainercv import utils
  from chainercv.links.model.yolo.yolo_base import YOLOBase
label_desc: Use image node_id 2 for calling the YOLOv3 obj's underlying member method code with example usage: obj.to_cpu() without return types