code: def _make_erb_filters(
      fs: int, num_freqs: int, cutoff: float, device: torch.device
  ) -> Tensor:
      from gammatone.filters import centre_freqs, make_erb_filters
  
      cfs = centre_freqs(fs, num_freqs, cutoff)
      fcoefs = make_erb_filters(fs, cfs)
      return torch.tensor(fcoefs, device=device)
  
file_path: torchmetrics/src/torchmetrics/functional/audio/srmr.py
imports: from functools import lru_cache
  from math import ceil, pi
  from typing import Optional, Tuple
  import torch
  from torch import Tensor
  from torch.nn.functional import pad
  from torchmetrics.utilities import rank_zero_warn
  from torchmetrics.utilities.imports import _GAMMATONE_AVAILABLE, _TORCHAUDIO_AVAILABLE, _TORCHAUDIO_GREATER_EQUAL_0_10
label_desc: Use image node_id 2 for calling a global function with example usage: _make_erb_filters(fs, num_freqs, cutoff, device) and returns: torch