code: def dummy_roi_average_align_2d(
      x, rois, roi_indices, outsize, spatial_scale, sampling_ratio=None
  ):
      if not isinstance(
          outsize, chainer.utils.collections_abc.Iterable
      ):
          outsize = outsize, outsize
  
      xp = backends.cuda.get_array_module(x.array)
      y = _random_array(
          xp, (len(rois), x.shape[1], outsize[0], outsize[1])
      )
      return chainer.Variable(y)
  
imports: from __future__ import division
  import mock
  import numpy
  import unittest
  import chainer
  from chainer import backends
  from chainer import testing
  from chainer.testing import attr
  from chainercv.links.model.fpn import BboxHead
  from chainercv.links.model.fpn import FasterRCNN
  from chainercv.links.model.fpn import MaskHead
  from chainercv.links.model.fpn import RPN
  from chainercv.utils import assert_is_bbox
  from chainercv.utils import assert_is_detection_link
  from chainercv.utils import assert_is_instance_segmentation_link
label_desc: Use image node_id 2 for calling a global function with example usage: dummy_roi_average_align_2d(x, rois, roi_indices, outsize, spatial_scale, sampling_ratio) and returns: chainer