class_docstr: Test suite for functions in `functional` module.
code: def test_create_mel_fb(
      self,
      n_mels=40,
      sample_rate=22050,
      n_fft=2048,
      fmin=0.0,
      fmax=8000.0,
      norm=None,
      mel_scale="htk",
  ):
      if norm == "slaney" and StrictVersion(
          librosa.__version__
      ) < StrictVersion("0.7.2"):
          self.skipTest(
              "Test is known to fail with older versions of librosa."
          )
      if self.device != "cpu":
          self.skipTest("No need to run this test on CUDA")
  
      expected = librosa.filters.mel(
          sr=sample_rate,
          n_fft=n_fft,
          n_mels=n_mels,
          fmax=fmax,
          fmin=fmin,
          htk=mel_scale == "htk",
          norm=norm,
      ).T
      result = F.melscale_fbanks(
          sample_rate=sample_rate,
          n_mels=n_mels,
          f_max=fmax,
          f_min=fmin,
          n_freqs=(n_fft // 2 + 1),
          norm=norm,
          mel_scale=mel_scale,
      )
      self.assertEqual(
          result, torch.from_numpy(expected), atol=7e-5, rtol=1.3e-6
      )
  
file_path: audio/test/torchaudio_unittest/functional/librosa_compatibility_test_impl.py
imports: import unittest
  from distutils.version import StrictVersion
  import torch
  import torchaudio.functional
  from parameterized import param
  from torchaudio._internal.module_utils import is_module_available
  from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, nested_params, TestBaseMixin
label_desc: Use image node_id 2 for calling the Functional obj's underlying member method code with example usage: obj.test_create_mel_fb(n_mels, sample_rate, n_fft, fmin, fmax, norm, mel_scale) without return types