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: Extend probabilities and states with more encoded chunks.
  
  Args:
      x (torch.Tensor): The extended encoder output feature
      hyps (Hypothesis): Current list of hypothesis
  
  Returns:
      Hypothesis: The extended hypothesis
docstr_tok: ["Extend","probabilities","and","states","with","more","encoded","chunks",".","Args",":","x","(","torch.Tensor",")",":","The","extended","encoder","output","feature","hyps","(","Hypothesis",")",":","Current","list","of","hypothesis","Returns",":","Hypothesis",":","The","extended","hypothesis"]
code: def extend(
      self, x: torch.Tensor, hyps: Hypothesis
  ) -> List[Hypothesis]:
      """Extend probabilities and states with more encoded chunks.
  
      Args:
          x (torch.Tensor): The extended encoder output feature
          hyps (Hypothesis): Current list of hypothesis
  
      Returns:
          Hypothesis: The extended hypothesis
  
      """
      for k, d in self.scorers.items():
          if hasattr(d, "extend_prob"):
              d.extend_prob(x)
          if hasattr(d, "extend_state"):
              hyps.states[k] = d.extend_state(hyps.states[k])
  
imports: import logging
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Tuple
  import torch
  from espnet2.asr.transducer.beam_search_transducer_streaming import BeamSearchTransducerStreaming
  from espnet.nets.batch_beam_search import BatchBeamSearch
  from espnet.nets.batch_beam_search import BatchHypothesis
  from espnet.nets.beam_search import Hypothesis
  from espnet.nets.beam_search_timesync_streaming import BeamSearchTimeSyncStreaming
  from espnet.nets.e2e_asr_common import end_detect
label_desc: Use image node_id 8 for calling the BatchBeamSearchOnline obj's underlying member method code with example usage: obj.extend(x, hyps) without return types