code: def test_best_metric_for_not_well_defined_metric_collection(
      base_metric,
  ):
      """Check for user warnings related to best metric.
  
      Test that if user tries to compute the best metric for a metric that does not have a well defined best, we throw an
      warning and return None.
  
      """
      tracker = MetricTracker(base_metric)
      for _ in range(3):
          tracker.increment()
          for _ in range(5):
              tracker.update(
                  torch.randint(3, (10,)), torch.randint(3, (10,))
              )
  
      with pytest.warns(
          UserWarning,
          match="Encountered the following error when trying to get the best metric.*",
      ):
          best = tracker.best_metric()
          if isinstance(best, dict):
              assert best["MulticlassAccuracy"] is not None
              assert best["MulticlassConfusionMatrix"] is None
          else:
              assert best is None
  
      with pytest.warns(
          UserWarning,
          match="Encountered the following error when trying to get the best metric.*",
      ):
          best, idx = tracker.best_metric(return_step=True)
  
          if isinstance(best, dict):
              assert best["MulticlassAccuracy"] is not None
              assert best["MulticlassConfusionMatrix"] is None
              assert idx["MulticlassAccuracy"] is not None
              assert idx["MulticlassConfusionMatrix"] is None
          else:
              assert best is None
              assert idx is None
  
file_path: torchmetrics/tests/unittests/wrappers/test_tracker.py
imports: import pytest
  import torch
  from torchmetrics import MetricCollection
  from torchmetrics.classification import MulticlassAccuracy, MulticlassConfusionMatrix, MulticlassPrecision, MulticlassRecall
  from torchmetrics.regression import MeanAbsoluteError, MeanSquaredError
  from torchmetrics.wrappers import MetricTracker, MultioutputWrapper
  from unittests.helpers import seed_all
label_desc: Use image node_id 4 for calling a global function with example usage: test_best_metric_for_not_well_defined_metric_collection(base_metric) without return types