code: def band_biquad(
      waveform: Tensor,
      sample_rate: int,
      central_freq: float,
      Q: float = 0.707,
      noise: bool = False,
  ) -> Tensor:
      r"""Design two-pole band filter.  Similar to SoX implementation.
  
      .. devices:: CPU CUDA
  
      .. properties:: Autograd TorchScript
  
      Args:
          waveform (Tensor): audio waveform of dimension of `(..., time)`
          sample_rate (int): sampling rate of the waveform, e.g. 44100 (Hz)
          central_freq (float or torch.Tensor): central frequency (in Hz)
          Q (float or torch.Tensor, optional): https://en.wikipedia.org/wiki/Q_factor (Default: ``0.707``).
          noise (bool, optional) : If ``True``, uses the alternate mode for un-pitched audio (e.g. percussion).
              If ``False``, uses mode oriented to pitched audio, i.e. voice, singing,
              or instrumental music (Default: ``False``).
  
      Returns:
          Tensor: Waveform of dimension of `(..., time)`
  
      Reference:
          - http://sox.sourceforge.net/sox.html
          - https://www.w3.org/2011/audio/audio-eq-cookbook.html#APF
      """
      dtype = waveform.dtype
      device = waveform.device
      central_freq = torch.as_tensor(
          central_freq, dtype=dtype, device=device
      )
      Q = torch.as_tensor(Q, dtype=dtype, device=device)
  
      w0 = 2 * math.pi * central_freq / sample_rate
      bw_Hz = central_freq / Q
  
      a0 = 1.0
      a2 = torch.exp(-2 * math.pi * bw_Hz / sample_rate)
      a1 = -4 * a2 / (1 + a2) * torch.cos(w0)
  
      b0 = torch.sqrt(1 - a1 * a1 / (4 * a2)) * (1 - a2)
  
      if noise:
          mult = (
              torch.sqrt(
                  ((1 + a2) * (1 + a2) - a1 * a1) * (1 - a2) / (1 + a2)
              )
              / b0
          )
          b0 = mult * b0
  
      b1 = 0.0
      b2 = 0.0
  
      return biquad(waveform, b0, b1, b2, a0, a1, a2)
  
imports: import math
  import warnings
  from typing import Optional
  import torch
  from torch import Tensor
  from torchaudio._extension import _IS_TORCHAUDIO_EXT_AVAILABLE
label_desc: Use image node_id 4 for calling a global function with example usage: band_biquad(waveform, sample_rate, central_freq, Q, noise) and returns: biquad