class_docstr: Sliding Window.
  
  Provides a sliding window over a batched continuous raw audio tensor.
  Optionally, provides padding (Currently not implemented).
  Combine this module with a pre-encoder compatible with raw audio data,
  for example Sinc convolutions.
  
  Known issues:
  Output length is calculated incorrectly if audio shorter than win_length.
  WARNING: trailing values are discarded - padding not implemented yet.
  There is currently no additional window function applied to input values.
docstr: Return output length of feature dimension D, i.e. the window length.
code: def output_size(self) -> int:
      """Return output length of feature dimension D, i.e. the window length."""
      return self.win_length
  
file_path: espnet/espnet2/asr/frontend/windowing.py
imports: from typing import Tuple
  import torch
  from typeguard import check_argument_types
  from espnet2.asr.frontend.abs_frontend import AbsFrontend
label_desc: Use image node_id 3 for calling the SlidingWindow obj's underlying member method code with example usage: obj.output_size() and returns: self