code: def forward(self, x, rois, roi_indices, img_size, gt_roi_label=None):
      n_roi = len(rois)
      ag_locs = chainer.Variable(_random_array(self.xp, (n_roi, 2, 4)))
      # For each bbox, the score for a selected class is
      # overwhelmingly higher than the scores for the other classes.
      ag_seg_scores = chainer.Variable(
          _random_array(
              self.xp, (n_roi, 2, self.roi_size, self.roi_size)
          )
      )
      score_idx = np.random.randint(
          low=0, high=self.n_class, size=(n_roi,)
      )
      cls_scores = self.xp.zeros(
          (n_roi, self.n_class), dtype=np.float32
      )
      cls_scores[np.arange(n_roi), score_idx] = 100
      cls_scores = chainer.Variable(cls_scores)
  
      return ag_seg_scores, ag_locs, cls_scores, rois, roi_indices
  
imports: import numpy
  import unittest
  import chainer
  from chainer import testing
  from chainer.testing import attr
  from chainercv.experimental.links.model.fcis import FCIS
  from chainercv.utils import assert_is_instance_segmentation_link
  from chainercv.utils import generate_random_bbox
label_desc: Use image node_id 2 for calling the DummyHead obj's underlying member method code with example usage: obj.forward(x, rois, roi_indices, img_size, gt_roi_label) and returns: ag_seg_scores,  ag_locs,  cls_scores,  rois,  roi_indices