code: def test_allowed_bbox_format_notations():
      notations = (
          "  lxyxy       ",
          "LxywH",
          *[
              "".join(it)
              for it in set(permutations(["l", "xy", "xy"], 3))
          ],
          *[
              "n" + "".join(it)
              for it in set(permutations(["l", "xy", "xy"], 3))
          ],
          *["".join(it) for it in permutations(["l", "xy", "wh"], 3)],
          *["".join(it) for it in permutations(["l", "xy", "wh"], 3)],
          *["".join(it) for it in permutations(["l", "cxcy", "wh"], 3)],
          *[
              "".join(it) + "n"
              for it in permutations(["l", "cxcy", "wh"], 3)
          ],
      )
  
      tokens = {
          "label",
          "width",
          "height",
          "xmin",
          "ymin",
          "xmax",
          "ymax",
          "xcenter",
          "ycenter",
      }
  
      for notation in notations:
          (
              are_coordinates_normalized,
              tokens,
          ) = verify_bbox_format_notation(notation)
          assert_that(len(set(tokens).difference(tokens)), equal_to(0))
          if "n" in notation:
              assert_that(are_coordinates_normalized is True)
  
imports: from itertools import permutations
  from typing import Union
  import numpy
  import torch
  from hamcrest import assert_that, calling, close_to, equal_to, raises
  from torch.utils.data import DataLoader, Dataset
  from deepchecks.vision.datasets.detection import coco_torch
  from deepchecks.vision.utils import image_properties
  from deepchecks.vision.utils.detection_formatters import convert_batch_of_bboxes, convert_bbox, verify_bbox_format_notation
  from deepchecks.vision.vision_data import VisionData
label_desc: Use image node_id 11 for calling a global function with example usage: test_allowed_bbox_format_notations() without return types