code: def test_mel(
      sample_rate, n_freq, n_mels, f_min, f_max_ratio, htk, norm
  ):
      f_max = int(f_max_ratio * (sample_rate // 2))
      mel_fb = KPB.filterbank_mel(
          sample_rate=sample_rate,
          n_freq=n_freq,
          n_mels=n_mels,
          f_min=f_min,
          f_max=f_max,
          htk=htk,
          norm=norm,
      )
      mel_fb = mel_fb.numpy()
  
      mel_fb_ref = librosa.filters.mel(
          sr=sample_rate,
          n_fft=(n_freq - 1) * 2,
          n_mels=n_mels,
          fmin=f_min,
          fmax=f_max,
          htk=htk,
          norm=norm,
      ).T
  
      assert mel_fb.dtype == K.floatx()
      assert mel_fb.shape == (n_freq, n_mels)
      np.testing.assert_allclose(mel_fb_ref, mel_fb)
  
file_path: kapre/tests/test_backend.py
imports: import pytest
  import numpy
  import librosa
  import tensorflow
  from tensorflow.keras import backend
  from kapre import backend
  from kapre.backend import magnitude_to_decibel, validate_data_format_str
  from utils import SRC
label_desc: Use image node_id 2 for calling a global function with example usage: test_mel(sample_rate, n_freq, n_mels, f_min, f_max_ratio, htk, norm) without return types