code: def _lfilter_core_generic_loop(
      input_signal_windows: Tensor,
      a_coeffs_flipped: Tensor,
      padded_output_waveform: Tensor,
  ):
      n_order = a_coeffs_flipped.size(1)
      a_coeffs_flipped = a_coeffs_flipped.unsqueeze(2)
      for i_sample, o0 in enumerate(
          input_signal_windows.permute(2, 0, 1)
      ):
          windowed_output_signal = padded_output_waveform[
              :, :, i_sample : i_sample + n_order
          ]
          o0 -= (
              windowed_output_signal.transpose(0, 1) @ a_coeffs_flipped
          )[..., 0].t()
          padded_output_waveform[:, :, i_sample + n_order - 1] = o0
  
imports: import math
  import warnings
  from typing import Optional
  import torch
  from torch import Tensor
  from torchaudio._extension import _IS_TORCHAUDIO_EXT_AVAILABLE
label_desc: Use image node_id 20 for calling a global function with example usage: _lfilter_core_generic_loop(input_signal_windows, a_coeffs_flipped, padded_output_waveform) without return types