code: def test_save_and_load_mel_spectrogram(self):
      mel_name = "mel_test"
      mel_featurizer = MelSpectrogramFeaturizer(
          feature_name=mel_name,
          mel_dim=self.spec_dim,
          hop_length=self.hop_len,
          sample_rate=self.sample_rate,
      )
  
      with self._create_test_dir() as test_dir:
          feature_dir = test_dir / "feature"
          mel_featurizer.save(
              manifest_entry=self.manifest_entry,
              audio_dir=test_dir,
              feature_dir=feature_dir,
          )
          mel_dict = mel_featurizer.load(
              manifest_entry=self.manifest_entry,
              audio_dir=test_dir,
              feature_dir=feature_dir,
          )
  
      mel_spec = mel_dict[mel_name]
      assert len(mel_spec.shape) == 2
      assert mel_spec.dtype == torch.float32
      assert mel_spec.shape[0] == self.spec_dim
      assert mel_spec.shape[1] == self.spec_len
  
imports: import contextlib
  import tempfile
  from pathlib import Path
  import numpy
  import pytest
  import soundfile
  import torch
  from nemo.collections.tts.parts.preprocessing.features import EnergyFeaturizer, MelSpectrogramFeaturizer, PitchFeaturizer
label_desc: Use image node_id 5 for calling the TestTTSFeatures obj's underlying member method code with example usage: obj.test_save_and_load_mel_spectrogram() without return types