code: def preemphasis(waveform, sample_rate: int, coeff: float = 0.97):
      """Pre-emphasize a waveform along the time dimension.
  
      y[i] = x[i] - coeff * x[i - 1]
  
      Args:
          waveform (torch.Tensor): audio signal (..., time)
          sample_rate (int): sampling rate in Hz (not used)
          coeff (float): pre-emphasis coefficient. Typically between 0.0 and 1.0.
  
      Returns:
          ret (torch.Tensor): pre-emphasized signal (..., time)
      """
      waveform = waveform.clone()
      waveform[..., 1:] -= coeff * waveform[..., :-1]
      return waveform
  
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 12 for calling a global function with example usage: preemphasis(waveform, sample_rate, coeff) and returns: waveform