code: def _buffered_arange(max) -> Tensor:
      """Compute arange using a buffered tensor across function calls.
      Produces same result as torch.arange(end=max).
  
      Args:
          max (int): Ending value for arange.
      """
      if not hasattr(_buffered_arange, "buf"):
          _buffered_arange.buf = torch.LongTensor()
      if max > _buffered_arange.buf.numel():
          _buffered_arange.buf.resize_(max)
          torch.arange(max, out=_buffered_arange.buf)
      return _buffered_arange.buf[:max]
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  from torch import nn, Tensor
  from torch.nn import Module, ModuleList
  from torchaudio.models import Wav2Vec2Model
  from torchaudio.models.conformer import ConformerLayer
  from torchaudio.models.rnnt import _TimeReduction
  from torchaudio.models.wav2vec2 import components
label_desc: Use image node_id 1 for calling a global function with example usage: _buffered_arange(max) and returns: _buffered_arange