code: def mel_frequencies(n_mels: int, fmin: float, fmax: float):
      """
      Return frequencies that are evenly spaced in mel scale.
  
      Args:
          n_mels (int): number of frequencies to return.
          fmin (float): start from this frequency (in Hz).
          fmax (float): finish at this frequency (in Hz).
  
  
      """
      low = hz_to_mel(torch.tensor(float(fmin))).item()
      high = hz_to_mel(torch.tensor(float(fmax))).item()
      mels = torch.linspace(low, high, n_mels)
      return mel_to_hz(mels)
  
file_path: julius/julius/core.py
imports: import math
  import typing
  import torch
  from torch.nn import functional
label_desc: Use image node_id 5 for calling a global function with example usage: mel_frequencies(n_mels, fmin, fmax) and returns: mel_to_hz