code: def _compute_label_frame(audio_frame: int) -> int:
      """Compute number of frames in the label tensor based on
      the number of frames in the audio tensor."""
      kernel_size = 25
      stride = 20
      sample_rate = 16  # 16 per millisecond
      label_frame = (
          math.floor(
              (audio_frame - kernel_size * sample_rate)
              / (stride * sample_rate)
          )
          + 1
      )
      return label_frame
  
imports: import math
  import os
  from typing import Tuple
  import torch
  import torch.nn.functional
  from parameterized import parameterized
  from torchaudio.models.wav2vec2 import hubert_base, hubert_large, hubert_pretrain_base, hubert_pretrain_large, hubert_pretrain_xlarge, hubert_xlarge, wav2vec2_base, wav2vec2_large, wav2vec2_large_lv60k, wavlm_base, wavlm_large
  from torchaudio_unittest.common_utils import skipIfNoCuda, skipIfNoQengine, torch_script, TorchaudioTestCase
label_desc: Use image node_id 2 for calling a global function with example usage: _compute_label_frame(audio_frame) and returns: label_frame