class_docstr: Online beam search implementation.
  
  This simulates streaming decoding.
  It requires encoded features of entire utterance and
  extracts block by block from it as it shoud be done
  in streaming processing.
  This is based on Tsunoo et al, "STREAMING TRANSFORMER ASR
  WITH BLOCKWISE SYNCHRONOUS BEAM SEARCH"
  (https://arxiv.org/abs/2006.14941).
docstr: Set hop size for streaming decoding.
  
  Args:
      hop_size (int): The hop size of encoder
docstr_tok: ["Set","hop","size","for","streaming","decoding",".","Args",":","hop_size","(","int",")",":","The","hop","size","of","encoder"]
code: def set_hop_size(self, hop_size: int):
      """Set hop size for streaming decoding.
  
      Args:
          hop_size (int): The hop size of encoder
      """
      self.hop_size = hop_size
  
file_path: espnet/espnet/nets/batch_beam_search_online_sim.py
imports: import logging
  from pathlib import Path
  from typing import List
  import torch
  import yaml
  from espnet.nets.batch_beam_search import BatchBeamSearch
  from espnet.nets.beam_search import Hypothesis
  from espnet.nets.e2e_asr_common import end_detect
label_desc: Use image node_id 3 for calling the BatchBeamSearchOnlineSim obj's underlying member method code with example usage: obj.set_hop_size(hop_size) without return types