code: def preemphasis(waveform, coeff: float = 0.97) -> torch.Tensor:
      r"""Pre-emphasizes a waveform along its last dimension, i.e.
      for each signal :math:`x` in ``waveform``, computes
      output :math:`y` as
  
      .. math::
          y[i] = x[i] - \text{coeff} \cdot x[i - 1]
  
      .. devices:: CPU CUDA
  
      .. properties:: Autograd TorchScript
  
      Args:
          waveform (torch.Tensor): Waveform, with shape `(..., N)`.
          coeff (float, optional): Pre-emphasis coefficient. Typically between 0.0 and 1.0.
              (Default: 0.97)
  
      Returns:
          torch.Tensor: Pre-emphasized waveform, with shape `(..., N)`.
      """
      waveform = waveform.clone()
      waveform[..., 1:] -= coeff * waveform[..., :-1]
      return waveform
  
imports: import math
  import tempfile
  import warnings
  from collections.abc import Sequence
  from typing import List, Optional, Tuple, Union
  import torch
  import torchaudio
  from torch import Tensor
  from torchaudio._internal.module_utils import deprecated
  from .filtering import highpass_biquad, treble_biquad
label_desc: Use image node_id 54 for calling a global function with example usage: preemphasis(waveform, coeff) and returns: waveform