code: def bandpass_filtering(
      waveform,
      sample_rate: int,
      center_freq: int = 3000,
      Q: float = 0.707,
      const_skirt_gain: bool = False,
  ):
      """Bandpass filter the input signal.
  
      Args:
          waveform (torch.Tensor): audio signal (..., time)
          sample_rate (int): sampling rate in Hz
          center_freq_freq (int): filter's center_freq frequency
          Q (float or torch.Tensor): https://en.wikipedia.org/wiki/Q_factor
          const_skirt_gain (bool): If True, uses a constant skirt gain (peak gain = Q).
              If False, uses a constant 0dB peak gain.
  
      Returns:
          ret (torch.Tensor): filtered signal (..., time)
      """
      ret = torchaudio.functional.bandpass_biquad(
          waveform,
          sample_rate,
          center_freq,
          Q=Q,
          const_skirt_gain=const_skirt_gain,
      )
      return ret
  
imports: import math
  import random
  from typing import Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  import torchaudio
label_desc: Use image node_id 4 for calling a global function with example usage: bandpass_filtering(waveform, sample_rate, center_freq, Q, const_skirt_gain) and returns: ret