code: def _skip_if_faster_coco_eval_missing(backend):
      if (
          backend == "faster_coco_eval"
          and not _FASTER_COCO_EVAL_AVAILABLE
      ):
          pytest.skip(
              "test requires that faster_coco_eval is installed"
          )
  
imports: import contextlib
  import io
  import json
  from copy import deepcopy
  from functools import partial
  from itertools import product
  import numpy
  import pytest
  import torch
  from lightning_utilities import apply_to_collection
  from pycocotools.coco import COCO
  from pycocotools.cocoeval import COCOeval
  from torch import IntTensor, Tensor
  from torchmetrics.detection.mean_ap import MeanAveragePrecision
  from torchmetrics.utilities.imports import _FASTER_COCO_EVAL_AVAILABLE, _PYCOCOTOOLS_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
  from unittests.detection import _DETECTION_BBOX, _DETECTION_SEGM, _DETECTION_VAL
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 1 for calling a global function with example usage: _skip_if_faster_coco_eval_missing(backend) without return types