code: def benchmark_resample_librosa(
      waveform,
      sample_rate,
      resample_rate,
      res_type=None,
      iters=5,
  ):
      waveform_np = waveform.squeeze().numpy()
      return (
          timeit.timeit(
              stmt="""
  librosa.resample(
      waveform_np,
      orig_sr=sample_rate,
      target_sr=resample_rate,
      res_type=res_type,
  )
          """,
              setup="import librosa",
              number=iters,
              globals=locals(),
          )
          * 1000
          / iters
      )
  
imports: import torch
  import torchaudio
  import torchaudio.functional
  import torchaudio.transforms
  import math
  import timeit
  import librosa
  import matplotlib.colors
  import matplotlib.pyplot
  import pandas
  import resampy
  from IPython.display import Audio
label_desc: Use image node_id 8 for calling a global function with example usage: benchmark_resample_librosa(waveform, sample_rate, resample_rate, res_type, iters) and returns: unknown