code: def deemphasis(waveform, coeff: float = 0.97) -> torch.Tensor:
      r"""De-emphasizes a waveform along its last dimension.
      Inverse of :meth:`preemphasis`. Concretely, for each signal
      :math:`x` in ``waveform``, computes output :math:`y` as
  
      .. math::
          y[i] = x[i] + \text{coeff} \cdot y[i - 1]
  
      .. devices:: CPU CUDA
  
      .. properties:: Autograd TorchScript
  
      Args:
          waveform (torch.Tensor): Waveform, with shape `(..., N)`.
          coeff (float, optional): De-emphasis coefficient. Typically between 0.0 and 1.0.
              (Default: 0.97)
  
      Returns:
          torch.Tensor: De-emphasized waveform, with shape `(..., N)`.
      """
      a_coeffs = torch.tensor(
          [1.0, -coeff], dtype=waveform.dtype, device=waveform.device
      )
      b_coeffs = torch.tensor(
          [1.0, 0.0], dtype=waveform.dtype, device=waveform.device
      )
      return torchaudio.functional.lfilter(
          waveform, a_coeffs=a_coeffs, b_coeffs=b_coeffs
      )
  
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 55 for calling a global function with example usage: deemphasis(waveform, coeff) and returns: torchaudio