code: def __call__(self, x, rois, roi_indices):
      # global context module
      h = self.global_context_module(x)
      # psroi max align
      pool = ps_roi_max_align_2d(
          h,
          rois,
          roi_indices,
          (10, self.roi_size, self.roi_size),
          self.spatial_scale,
          self.roi_size,
          sampling_ratio=2,
      )
      pool = F.where(
          self.xp.isinf(pool.array),
          self.xp.zeros(pool.shape, dtype=pool.dtype),
          pool,
      )
  
      # fc
      fc1 = F.relu(self.fc1(pool))
      roi_cls_locs = self.cls_loc(fc1)
      roi_scores = self.score(fc1)
      return roi_cls_locs, roi_scores
  
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 LightHeadRCNNResNet101Head obj's underlying member method code with example usage: obj.__call__(x, rois, roi_indices) and returns: roi_cls_locs,  roi_scores