






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


snake_case__   :						Optional[Any]													=   logging.get_logger(__name__)

snake_case__   :						Optional[Any]													=   {"""vocab_file""": """spiece.model"""}

snake_case__   :						Dict													=   {
    """vocab_file""": {
        """bert_for_seq_generation""": (
            """https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"""
        ),
    }
}

snake_case__   :						Tuple													=   {"""bert_for_seq_generation""": 5_1_2}


class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  A_						       = VOCAB_FILES_NAMES
  A_						       = PRETRAINED_VOCAB_FILES_MAP
  A_						       = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A_						       = []
  A_						       = ["""input_ids""", """attention_mask"""]




  def __init__(  self		,		_UpperCAmelCase		,		_UpperCAmelCase="<s>"		,		_UpperCAmelCase="</s>"		,		_UpperCAmelCase="<unk>"		,		_UpperCAmelCase="<pad>"		,		_UpperCAmelCase="<::::>"		,		_UpperCAmelCase = None		,		**_UpperCAmelCase		,		)      ->			None:
     UpperCamelCase_						=  {} if sp_model_kwargs is None else sp_model_kwargs

     # Add extra_ids to the special token list
     super().__init__(
         bos_token=_UpperCAmelCase		,		eos_token=_UpperCAmelCase		,		unk_token=_UpperCAmelCase		,		pad_token=_UpperCAmelCase		,		sep_token=_UpperCAmelCase		,		sp_model_kwargs=self.sp_model_kwargs		,		**_UpperCAmelCase		,		)

     UpperCamelCase_						=  vocab_file

     UpperCamelCase_						=  spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.Load(_UpperCAmelCase			)




  @property
  def  _UpperCAmelCase  (  self			)      ->			Union[str, Any]:
     return self.sp_model.get_piece_size()




  def  _UpperCAmelCase  (  self			)      ->			int:
     UpperCamelCase_						=  {self.convert_ids_to_tokens(_UpperCAmelCase			): i for i in range(self.vocab_size			)}
     vocab.update(self.added_tokens_encoder			)
     return vocab




  def __getstate__(  self			)      ->			str:
     UpperCamelCase_						=  self.__dict__.copy()
     UpperCamelCase_						=  None
     return state




  def __setstate__(  self		,		_UpperCAmelCase			)      ->			List[str]:
     UpperCamelCase_						=  d

     # for backward compatibility
     if not hasattr(self		,		'sp_model_kwargs'			):
        UpperCamelCase_						=  {}

     UpperCamelCase_						=  spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.Load(self.vocab_file			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			List[str]:
     return self.sp_model.encode(_UpperCAmelCase		,		out_type=_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			Union[str, Any]:
     return self.sp_model.piece_to_id(_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			Optional[int]:
     UpperCamelCase_						=  self.sp_model.IdToPiece(_UpperCAmelCase			)
     return token




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			Union[str, Any]:
     UpperCamelCase_						=  []
     UpperCamelCase_						=  ''
     for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
           out_string += self.sp_model.decode(_UpperCAmelCase			) + token
           UpperCamelCase_						=  []
        else:
           current_sub_tokens.append(_UpperCAmelCase			)
     out_string += self.sp_model.decode(_UpperCAmelCase			)
     return out_string.strip()




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = None			)      ->			Tuple[str]:
     if not os.path.isdir(_UpperCAmelCase			):
        logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""			)
        return
     UpperCamelCase_						=  os.path.join(
         _UpperCAmelCase		,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)

     if os.path.abspath(self.vocab_file			) != os.path.abspath(_UpperCAmelCase			) and os.path.isfile(self.vocab_file			):
        copyfile(self.vocab_file		,		_UpperCAmelCase			)
     elif not os.path.isfile(self.vocab_file			):
        with open(_UpperCAmelCase		,		'wb'			) as fi:
           UpperCamelCase_						=  self.sp_model.serialized_model_proto()
           fi.write(_UpperCAmelCase			)

     return (out_vocab_file,)













from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

snake_case__   :						Dict													=   TypeVar("""T""")


class     _a							(	Generic[T]     ):






  """simple docstring"""





  A_						       = 42  # Cache store of keys
  A_						       = 42  # References of the keys in cache
  A_						       = 10  # Maximum capacity of cache




  def __init__(  self		,		_UpperCAmelCase			)      ->			None:
     UpperCamelCase_						=  deque()
     UpperCamelCase_						=  set()
     if not n:
        UpperCamelCase_						=  sys.maxsize
     elif n < 0:
        raise ValueError('n should be an integer greater than 0.'			)
     else:
        UpperCamelCase_						=  n




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			None:
     if x not in self.key_reference:
        if len(self.dq_store			) == LRUCache._MAX_CAPACITY:
           UpperCamelCase_						=  self.dq_store.pop()
           self.key_reference.remove(_UpperCAmelCase			)
     else:
        self.dq_store.remove(_UpperCAmelCase			)

     self.dq_store.appendleft(_UpperCAmelCase			)
     self.key_reference.add(_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self			)      ->			None:
     for k in self.dq_store:
        print(_UpperCAmelCase			)




  def __repr__(  self			)      ->			str:
     return f"""LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store			)}"""


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 snake_case__   :						LRUCache[str | int]													=   LRUCache(4)
 lru_cache.refer("""A""")
 lru_cache.refer(2)
 lru_cache.refer(3)
 lru_cache.refer("""A""")
 lru_cache.refer(4)
 lru_cache.refer(5)
 lru_cache.display()

 print(lru_cache)
 assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"





