code: def __init__(
      self,
      n_class,
      roi_size,
      spatial_scale,
      global_module_initialW=None,
      loc_initialW=None,
      score_initialW=None,
  ):
      super(LightHeadRCNNResNet101Head, self).__init__()
      self.n_class = n_class
      self.spatial_scale = spatial_scale
      self.roi_size = roi_size
      with self.init_scope():
          self.global_context_module = GlobalContextModule(
              2048,
              256,
              self.roi_size * self.roi_size * 10,
              15,
              initialW=global_module_initialW,
          )
          self.fc1 = L.Linear(
              self.roi_size * self.roi_size * 10,
              2048,
              initialW=score_initialW,
          )
          self.score = L.Linear(2048, n_class, initialW=score_initialW)
          self.cls_loc = L.Linear(
              2048, 4 * n_class, initialW=loc_initialW
          )
  
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 1 to create a new LightHeadRCNNResNet101Head object from inherited base classes: chainer with example: obj = LightHeadRCNNResNet101Head(n_class, roi_size, spatial_scale, global_module_initialW, loc_initialW, score_initialW)