code: def _check_call(self):
      hs = [
          chainer.Variable(
              _random_array(self.link.xp, (2, 64, 32, 32))
          ),
          chainer.Variable(
              _random_array(self.link.xp, (2, 64, 16, 16))
          ),
          chainer.Variable(_random_array(self.link.xp, (2, 64, 8, 8))),
      ]
      rois = [
          self.link.xp.array(((4, 1, 6, 3),), dtype=np.float32),
          self.link.xp.array(
              ((0, 1, 2, 3), (5, 4, 10, 6)), dtype=np.float32
          ),
          self.link.xp.array(((10, 4, 12, 10),), dtype=np.float32),
      ]
      roi_indices = [
          self.link.xp.array((0,), dtype=np.int32),
          self.link.xp.array((1, 0), dtype=np.int32),
          self.link.xp.array((1,), dtype=np.int32),
      ]
  
      locs, confs = self.link(hs, rois, roi_indices)
  
      self.assertIsInstance(locs, chainer.Variable)
      self.assertIsInstance(locs.array, self.link.xp.ndarray)
      self.assertEqual(locs.shape, (4, self.n_class, 4))
  
      self.assertIsInstance(confs, chainer.Variable)
      self.assertIsInstance(confs.array, self.link.xp.ndarray)
      self.assertEqual(confs.shape, (4, self.n_class))
  
imports: from __future__ import division
  import numpy
  import unittest
  import chainer
  from chainer import testing
  from chainer.testing import attr
  from chainercv.links.model.fpn import bbox_head_loss_post
  from chainercv.links.model.fpn import bbox_head_loss_pre
  from chainercv.links.model.fpn import BboxHead
label_desc: Use image node_id 2 for calling the TestBboxHead obj's underlying member method code with example usage: obj._check_call() without return types