class_docstr: A Darknet19 based feature extractor for YOLOv2.
  
  This is a feature extractor for :class:`~chainercv.links.model.yolo.YOLOv2`
class_docstr_tok: ["A","Darknet19","based","feature","extractor","for","YOLOv2",".","This","is","a","feature","extractor","for",":","class",":","`","~chainercv.links.model.yolo.YOLOv2","`"]
code: def __init__(self):
      super(Darknet19Extractor, self).__init__()
  
      # Darknet19
      for k, n_conv in enumerate((1, 1, 3, 3, 5, 5)):
          for i in range(n_conv):
              if i % 2 == 0:
                  self.append(
                      Conv2DBNActiv(
                          32 << k, 3, pad=1, activ=_leaky_relu
                      )
                  )
              else:
                  self.append(
                      Conv2DBNActiv(32 << (k - 1), 1, activ=_leaky_relu)
                  )
  
      # additional links
      self.append(Conv2DBNActiv(1024, 3, pad=1, activ=_leaky_relu))
      self.append(Conv2DBNActiv(1024, 3, pad=1, activ=_leaky_relu))
      self.append(Conv2DBNActiv(64, 1, activ=_leaky_relu))
      self.append(Conv2DBNActiv(1024, 3, pad=1, activ=_leaky_relu))
  
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 1 to create a new Darknet19Extractor object from inherited base classes: chainer with example: obj = Darknet19Extractor()