


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


__UpperCAmelCase : List[Any] 			=				logging.get_logger(__name__)

__UpperCAmelCase : Any 			=				{"vocab_file": "spiece.model"}

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

__UpperCAmelCase : Optional[Any] 			=				{"bert_for_seq_generation": 512}



class    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     int							=					VOCAB_FILES_NAMES
       __UpperCamelCase      :     Union[str, Any]							=					PRETRAINED_VOCAB_FILES_MAP
       __UpperCamelCase      :     int							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __UpperCamelCase      :     List[int]							=					[]
       __UpperCamelCase      :     Any							=					["input_ids", "attention_mask"]






       def __init__(     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE="<s>" ,					__SCREAMING_SNAKE_CASE="</s>" ,					__SCREAMING_SNAKE_CASE="<unk>" ,					__SCREAMING_SNAKE_CASE="<pad>" ,					__SCREAMING_SNAKE_CASE="<::::>" ,					__SCREAMING_SNAKE_CASE = None ,					**__SCREAMING_SNAKE_CASE ,					):




              """simple docstring"""




              UpperCamelCase    :	Any   	=		{} if sp_model_kwargs is None else sp_model_kwargs

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

              UpperCamelCase    :	str   	=		vocab_file

              UpperCamelCase    :	List[Any]   	=		spm.SentencePieceProcessor(**self.sp_model_kwargs						)
              self.sp_model.Load(__SCREAMING_SNAKE_CASE						)






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return self.sp_model.get_piece_size()






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		{self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE						): i for i in range(self.vocab_size						)}
              vocab.update(self.added_tokens_encoder						)
              return vocab






       def __getstate__(     self						):




              """simple docstring"""




              UpperCamelCase    :	int   	=		self.__dict__.copy()
              UpperCamelCase    :	Optional[Any]   	=		None
              return state






       def __setstate__(     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		d

              # for backward compatibility
              if not hasattr(self ,					'''sp_model_kwargs'''						):
                     UpperCamelCase    :	Union[str, Any]   	=		{}

              UpperCamelCase    :	List[str]   	=		spm.SentencePieceProcessor(**self.sp_model_kwargs						)
              self.sp_model.Load(self.vocab_file						)






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return self.sp_model.encode(__SCREAMING_SNAKE_CASE ,					out_type=__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return self.sp_model.piece_to_id(__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	Union[str, Any]   	=		self.sp_model.IdToPiece(__SCREAMING_SNAKE_CASE						)
              return token






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	Union[str, Any]   	=		[]
              UpperCamelCase    :	Any   	=		''''''
              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(__SCREAMING_SNAKE_CASE						) + token
                            UpperCamelCase    :	List[str]   	=		[]
                     else:
                            current_sub_tokens.append(__SCREAMING_SNAKE_CASE						)
              out_string += self.sp_model.decode(__SCREAMING_SNAKE_CASE						)
              return out_string.strip()






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE = None						):




              """simple docstring"""




              if not os.path.isdir(__SCREAMING_SNAKE_CASE						):
                     logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""						)
                     return
              UpperCamelCase    :	int   	=		os.path.join(
                  __SCREAMING_SNAKE_CASE ,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

              if os.path.abspath(self.vocab_file						) != os.path.abspath(__SCREAMING_SNAKE_CASE						) and os.path.isfile(self.vocab_file						):
                     copyfile(self.vocab_file ,					__SCREAMING_SNAKE_CASE						)
              elif not os.path.isfile(self.vocab_file						):
                     with open(__SCREAMING_SNAKE_CASE ,					'''wb'''						) as fi:
                            UpperCamelCase    :	Optional[int]   	=		self.sp_model.serialized_model_proto()
                            fi.write(__SCREAMING_SNAKE_CASE						)

              return (out_vocab_file,)





def      a	(							SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





       if number > 0:
              raise ValueError('''input must be a negative integer'''       )
       UpperCamelCase    :	List[str]   	=		len(bin(SCREAMING_SNAKE_CASE_       )[3:]       )
       UpperCamelCase    :	List[str]   	=		bin(abs(SCREAMING_SNAKE_CASE_       ) - (1 << binary_number_length)       )[3:]
       UpperCamelCase    :	Dict   	=		(
           (
               '''1'''
               + '''0''' * (binary_number_length - len(SCREAMING_SNAKE_CASE_       ))
               + twos_complement_number
           )
           if number < 0
           else '''0'''
       )
       return "0b" + twos_complement_number


if __name__ == "__main__":
  import doctest

  doctest.testmod()

