class_docstr: SentencePiece-model-based token processor.
  
  Args:
      sp_model_path (str): path to SentencePiece model.
class_docstr_tok: ["SentencePiece-model-based","token","processor",".","Args",":","sp_model_path","(","str",")",":","path","to","SentencePiece","model","."]
docstr: Decodes given list of tokens to text sequence.
  
  Args:
      tokens (List[int]): list of tokens to decode.
      lstrip (bool, optional): if ``True``, returns text sequence with leading whitespace
          removed. (Default: ``True``).
  
  Returns:
      str:
          Decoded text sequence.
docstr_tok: ["Decodes","given","list","of","tokens","to","text","sequence",".","Args",":","tokens","(","List","[","int","]",")",":","list","of","tokens","to","decode",".","lstrip","(","bool",",","optional",")",":","if","``","True","``",",","returns","text","sequence","with","leading","whitespace","removed",".","(","Default",":","``","True","``",")",".","Returns",":","str",":","Decoded","text","sequence","."]
code: def __call__(self, tokens: List[int], lstrip: bool = True) -> str:
      """Decodes given list of tokens to text sequence.
  
      Args:
          tokens (List[int]): list of tokens to decode.
          lstrip (bool, optional): if ``True``, returns text sequence with leading whitespace
              removed. (Default: ``True``).
  
      Returns:
          str:
              Decoded text sequence.
      """
      filtered_hypo_tokens = [
          token_index
          for token_index in tokens[1:]
          if token_index not in self.post_process_remove_list
      ]
      output_string = "".join(
          self.sp_model.id_to_piece(filtered_hypo_tokens)
      ).replace("\u2581", " ")
  
      if lstrip:
          return output_string.lstrip()
      else:
          return output_string
  
imports: import json
  import math
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from functools import partial
  from typing import Callable, List, Tuple
  import torch
  import torchaudio
  from torchaudio._internal import module_utils
  from torchaudio.models import emformer_rnnt_base, RNNT, RNNTBeamSearch
label_desc: Use image node_id 2 for calling the _SentencePieceTokenProcessor obj's underlying member method code with example usage: obj.__call__(tokens, lstrip) and returns: output_string, output_string