code: def test_melfbnorm(infile):
      DATA = load(infile)
      # if DATA['norm'] is empty, pass None.
      if DATA["norm"].shape[-1] == 0:
          norm = None
      else:
          norm = DATA["norm"][0, 0]
      wts = librosa.filters.mel(
          sr=DATA["sr"][0, 0],
          n_fft=DATA["nfft"][0, 0],
          n_mels=DATA["nfilts"][0, 0],
          fmin=DATA["fmin"][0, 0],
          fmax=DATA["fmax"][0, 0],
          htk=DATA["htk"][0, 0],
          norm=norm,
      )
      # Pad out.
      wts = np.pad(
          wts,
          [(0, 0), (0, DATA["nfft"][0, 0] // 2 - 1)],
          mode="constant",
      )
  
      assert wts.shape == DATA["wts"].shape
      assert np.allclose(wts, DATA["wts"])
  
imports: import os
  from contextlib import nullcontext
  import warnings
  import glob
  import numpy
  import scipy.io
  import scipy.signal
  from typing import Any, ContextManager
  import pytest
  import librosa
label_desc: Use image node_id 7 for calling a global function with example usage: test_melfbnorm(infile) without return types