code: def _mel_to_hz(mels: Tensor, mel_scale: str = "htk") -> Tensor:
      """Convert mel bin numbers to frequencies.
  
      Args:
          mels (Tensor): Mel frequencies
          mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)
  
      Returns:
          freqs (Tensor): Mels converted in Hz
      """
  
      if mel_scale not in ["slaney", "htk"]:
          raise ValueError(
              'mel_scale should be one of "htk" or "slaney".'
          )
  
      if mel_scale == "htk":
          return 700.0 * (10.0 ** (mels / 2595.0) - 1.0)
  
      # Fill in the linear scale
      f_min = 0.0
      f_sp = 200.0 / 3
      freqs = f_min + f_sp * mels
  
      # And now the nonlinear scale
      min_log_hz = 1000.0
      min_log_mel = (min_log_hz - f_min) / f_sp
      logstep = math.log(6.4) / 27.0
  
      log_t = mels >= min_log_mel
      freqs[log_t] = min_log_hz * torch.exp(
          logstep * (mels[log_t] - min_log_mel)
      )
  
      return freqs
  
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 9 for calling a global function with example usage: _mel_to_hz(mels, mel_scale) and returns: freqs, unknown