class_docstr: ResNet101 Extractor for Light-Head R-CNN ResNet101 implementation.
  
  This class is used as an extractor for LightHeadRCNNResNet101.
  This outputs feature maps.
  
  Args:
      initialW: Initializer for ResNet101 extractor.
class_docstr_tok: ["ResNet101","Extractor","for","Light-Head","R-CNN","ResNet101","implementation",".","This","class","is","used","as","an","extractor","for","LightHeadRCNNResNet101",".","This","outputs","feature","maps",".","Args",":","initialW",":","Initializer","for","ResNet101","extractor","."]
docstr: Forward the chain.
  
  Args:
      x (~chainer.Variable): 4D image variable.
docstr_tok: ["Forward","the","chain",".","Args",":","x","(","~chainer.Variable",")",":","4D","image","variable","."]
code: def __call__(self, x):
      """Forward the chain.
  
      Args:
          x (~chainer.Variable): 4D image variable.
  
      """
  
      with chainer.using_config("train", False):
          h = self.pool1(self.conv1(x))
          h = self.res2(h)
          h.unchain_backward()
          h = self.res3(h)
          res4 = self.res4(h)
          res5 = self.res5(res4)
      return res4, res5
  
imports: from __future__ import division
  import numpy
  import chainer
  import chainer.functions
  import chainer.links
  from chainercv.functions import ps_roi_max_align_2d
  from chainercv.links.connection.conv_2d_bn_activ import Conv2DBNActiv
  from chainercv.links.model.faster_rcnn.region_proposal_network import RegionProposalNetwork
  from chainercv.links.model.light_head_rcnn.global_context_module import GlobalContextModule
  from chainercv.links.model.light_head_rcnn.light_head_rcnn import LightHeadRCNN
  from chainercv.links.model.resnet.resblock import ResBlock
  from chainercv.links.model.resnet.resnet import ResNet101
  from chainercv import utils
label_desc: Use image node_id 2 for calling the ResNet101Extractor obj's underlying member method code with example usage: obj.__call__(x) and returns: res4,  res5