code: def test_iou_extreme(self):
      # Cause floating point issues in cuda kernels (#1266)
      for device in ["cpu"] + (
          ["cuda"] if torch.cuda.is_available() else []
      ):
          boxes1 = torch.tensor(
              [[160.0, 153.0, 230.0, 23.0, -37.0]], device=device
          )
          boxes2 = torch.tensor(
              [
                  [
                      -1.117407639806935e17,
                      1.3858420478349148e18,
                      1000.0000610351562,
                      1000.0000610351562,
                      1612.0,
                  ]
              ],
              device=device,
          )
          ious = pairwise_iou_rotated(boxes1, boxes2)
          self.assertTrue(ious.min() >= 0, ious)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import math
  import random
  import unittest
  import torch
  from fvcore.common.benchmark import benchmark
  from detectron2.layers.rotated_boxes import pairwise_iou_rotated
  from detectron2.structures.boxes import Boxes
  from detectron2.structures.rotated_boxes import RotatedBoxes, pairwise_iou
  from detectron2.utils.testing import reload_script_model
label_desc: Use image node_id 7 for calling the TestRotatedBoxesLayer obj's underlying member method code with example usage: obj.test_iou_extreme() without return types