code: def test_extreme_values():
      """Test that the metric returns expected values in trivial cases."""
      # Exact match between preds and target => metric is 1
      assert (
          modified_panoptic_quality(
              _INPUTS_0.target[0], _INPUTS_0.target[0], **_ARGS_0
          )
          == 1.0
      )
      # Every element of the prediction is wrong => metric is 0
      assert (
          modified_panoptic_quality(
              _INPUTS_0.target[0], _INPUTS_0.target[0] + 1, **_ARGS_0
          )
          == 0.0
      )
  
file_path: torchmetrics/tests/unittests/detection/test_modified_panoptic_quality.py
imports: from typing import Any, Dict
  import numpy
  import pytest
  import torch
  from torchmetrics.detection import ModifiedPanopticQuality
  from torchmetrics.functional.detection import modified_panoptic_quality
  from unittests import _Input
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 6 for calling a global function with example usage: test_extreme_values() without return types