code: def test_punct_capit_with_distilbert(self):
      data_dir = (
          "/home/TestData/nlp/token_classification_punctuation/fisher"
      )
      model = models.PunctuationCapitalizationModel.from_pretrained(
          "punctuation_en_distilbert"
      )
      metrics = get_metrics_new_format(data_dir, model)
  
      assert abs(metrics["test_punct_precision"] - 53.0826) < 0.001
      assert abs(metrics["test_punct_recall"] - 56.2905) < 0.001
      assert abs(metrics["test_punct_f1"] - 52.4225) < 0.001
      assert (
          int(
              model.metrics["test"]["punct_class_report"][
                  0
              ].total_examples
          )
          == 128
      )
  
file_path: NeMo/tests/collections/nlp/test_pretrained_models_performance.py
imports: import os
  from pathlib import Path
  from shutil import rmtree
  from unittest import TestCase
  import pytest
  import pytorch_lightning
  from omegaconf import OmegaConf
  import nemo.collections.nlp.models
label_desc: Use image node_id 2 for calling the TestPretrainedModelPerformance obj's underlying member method code with example usage: obj.test_punct_capit_with_distilbert() without return types