code: def deemphasis(waveform, sample_rate: int, coeff: float = 0.97):
      """De-emphasize a waveform along the time dimension.
  
      y[i] = x[i] + coeff * y[i - 1]
  
      Args:
          waveform (torch.Tensor): audio signal (..., time)
          sample_rate (int): sampling rate in Hz (not used)
          coeff (float): de-emphasis coefficient. Typically between 0.0 and 1.0.
  
      Returns:
          ret (torch.Tensor): de-emphasized signal (..., time)
      """
      a_coeffs = waveform.new_tensor([1.0, -coeff])
      b_coeffs = waveform.new_tensor([1.0, 0.0])
      return torchaudio.functional.lfilter(
          waveform, a_coeffs=a_coeffs, b_coeffs=b_coeffs
      )
  
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 13 for calling a global function with example usage: deemphasis(waveform, sample_rate, coeff) and returns: torchaudio