code: def deemph_biquad(waveform: Tensor, sample_rate: int) -> Tensor:
      r"""Apply ISO 908 CD de-emphasis (shelving) IIR 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, Allowed sample rate ``44100`` or ``48000``
  
      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
      """
  
      if sample_rate == 44100:
          central_freq = 5283
          width_slope = 0.4845
          gain = -9.477
      elif sample_rate == 48000:
          central_freq = 5356
          width_slope = 0.479
          gain = -9.62
      else:
          raise ValueError(
              "Sample rate must be 44100 (audio-CD) or 48000 (DAT)"
          )
  
      w0 = 2 * math.pi * central_freq / sample_rate
      A = math.exp(gain / 40.0 * math.log(10))
      alpha = (
          math.sin(w0)
          / 2
          * math.sqrt((A + 1 / A) * (1 / width_slope - 1) + 2)
      )
  
      temp1 = 2 * math.sqrt(A) * alpha
      temp2 = (A - 1) * math.cos(w0)
      temp3 = (A + 1) * math.cos(w0)
  
      b0 = A * ((A + 1) + temp2 + temp1)
      b1 = -2 * A * ((A - 1) + temp3)
      b2 = A * ((A + 1) + temp2 - temp1)
      a0 = (A + 1) - temp2 + temp1
      a1 = 2 * ((A - 1) - temp3)
      a2 = (A + 1) - temp2 - temp1
  
      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 11 for calling a global function with example usage: deemph_biquad(waveform, sample_rate) and returns: biquad