docstr: Test using the metric in the same way as Evaluator.
docstr_tok: ["Test","using","the","metric","in","the","same","way","as","Evaluator","."]
code: def _test_evaluate(self, format_only, outfile_predix=None):
      """Test using the metric in the same way as Evaluator."""
      metric = MOTChallengeMetric(
          metric=["HOTA", "CLEAR", "Identity"],
          format_only=format_only,
          outfile_prefix=outfile_predix,
      )
      metric.dataset_meta = {"classes": ("pedestrian",)}
      data_batch = dict(input=None, data_samples=None)
      predictions = self._get_predictions_demo()
      metric.process(data_batch, predictions)
      eval_results = metric.evaluate()
      return eval_results
  
file_path: mmdetection/tests/test_evaluation/test_metrics/test_mot_challenge_metrics.py
imports: import copy
  import os
  import tempfile
  from unittest import TestCase
  import torch
  from mmengine.structures import BaseDataElement, InstanceData
  from mmdet.evaluation import MOTChallengeMetric
  from mmdet.structures import DetDataSample, TrackDataSample
label_desc: Use image node_id 4 for calling the TestMOTChallengeMetric obj's underlying member method code with example usage: obj._test_evaluate(format_only, outfile_predix) and returns: eval_results