


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__				:	str					       =					logging.get_logger(__name__)


snake_case__				:	Tuple					       =					"""▁"""

snake_case__				:	Union[str, Any]					       =					{"""vocab_file""": """spiece.model"""}

snake_case__				:	List[Any]					       =					{
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    }
}

snake_case__				:	Optional[int]					       =					{
    """google/reformer-crime-and-punishment""": 52_4288,
}





class   SCREAMING_SNAKE_CASE_			(a__						):




       '''simple docstring'''



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



       def __init__(						self				:				Optional[Any]		,				__a				:				int		,				__a				:				List[str]="</s>"		,				__a				:				List[Any]="<unk>"		,				__a				:				str=[]		,				__a				:				List[Any] = None		,				**__a				:				Optional[Any]		,				)					->int:
          lowerCamelCase_						:   int		= {} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              eos_token=__lowerCAmelCase		,				unk_token=__lowerCAmelCase		,				additional_special_tokens=__lowerCAmelCase		,				sp_model_kwargs=self.sp_model_kwargs		,				**__lowerCAmelCase		,				)

          lowerCamelCase_						:   Optional[Any]		= vocab_file
          lowerCamelCase_						:   int		= spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.Load(__lowerCAmelCase							)



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



       def 				_lowerCAmelCase							(						self				:				str							)					->List[Any]:
          lowerCamelCase_						:   str		= {self.convert_ids_to_tokens(__lowerCAmelCase							): i for i in range(self.vocab_size							)}
          vocab.update(self.added_tokens_encoder							)
          return vocab



       def __getstate__(						self				:				int							)					->Dict:
          lowerCamelCase_						:   Optional[Any]		= self.__dict__.copy()
          lowerCamelCase_						:   Optional[Any]		= None
          return state



       def __setstate__(						self				:				Any		,				__a				:				Any							)					->Any:
          lowerCamelCase_						:   Any		= d

          # for backward compatibility
          if not hasattr(self		,				"""sp_model_kwargs"""							):
             lowerCamelCase_						:   Optional[int]		= {}

          lowerCamelCase_						:   Union[str, Any]		= spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.Load(self.vocab_file							)



       def 				_lowerCAmelCase							(						self				:				Tuple		,				__a				:				Tuple							)					->List[Any]:
          return self.sp_model.encode(__lowerCAmelCase		,				out_type=__lowerCAmelCase							)



       def 				_lowerCAmelCase							(						self				:				Optional[int]		,				__a				:				Optional[int]							)					->List[str]:
          return self.sp_model.piece_to_id(__lowerCAmelCase							)



       def 				_lowerCAmelCase							(						self				:				Dict		,				__a				:				Dict							)					->Dict:
          if index < self.sp_model.get_piece_size():
             lowerCamelCase_						:   int		= self.sp_model.IdToPiece(__lowerCAmelCase							)
          return token



       def 				_lowerCAmelCase							(						self				:				Dict		,				__a				:				int							)					->Optional[int]:
          lowerCamelCase_						:   Optional[Any]		= []
          lowerCamelCase_						:   Tuple		= ''''''
          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(__lowerCAmelCase							) + token
                lowerCamelCase_						:   Optional[Any]		= []
             else:
                current_sub_tokens.append(__lowerCAmelCase							)
          out_string += self.sp_model.decode(__lowerCAmelCase							)
          return out_string.strip()




       def 				_lowerCAmelCase							(						self				:				Tuple		,				__a				:				List[Any]		,				__a				:				int = None							)					->List[str]:
          if not os.path.isdir(__lowerCAmelCase							):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
             return
          lowerCamelCase_						:   Optional[int]		= os.path.join(
              __lowerCAmelCase		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

          if os.path.abspath(self.vocab_file							) != os.path.abspath(__lowerCAmelCase							) and os.path.isfile(self.vocab_file							):
             copyfile(self.vocab_file		,				__lowerCAmelCase							)
          elif not os.path.isfile(self.vocab_file							):
             with open(__lowerCAmelCase		,				"""wb"""							) as fi:
                lowerCamelCase_						:   Dict		= self.sp_model.serialized_model_proto()
                fi.write(__lowerCAmelCase							)

          return (out_vocab_file,)













SCREAMING_SNAKE_CASE__   :      Tuple				=		{
    """a""": """AAAAA""",
    """b""": """AAAAB""",
    """c""": """AAABA""",
    """d""": """AAABB""",
    """e""": """AABAA""",
    """f""": """AABAB""",
    """g""": """AABBA""",
    """h""": """AABBB""",
    """i""": """ABAAA""",
    """j""": """BBBAA""",
    """k""": """ABAAB""",
    """l""": """ABABA""",
    """m""": """ABABB""",
    """n""": """ABBAA""",
    """o""": """ABBAB""",
    """p""": """ABBBA""",
    """q""": """ABBBB""",
    """r""": """BAAAA""",
    """s""": """BAAAB""",
    """t""": """BAABA""",
    """u""": """BAABB""",
    """v""": """BBBAB""",
    """w""": """BABAA""",
    """x""": """BABAB""",
    """y""": """BABBA""",
    """z""": """BABBB""",
    """ """: """ """,
}


SCREAMING_SNAKE_CASE__   :      Union[str, Any]				=		{value: key for key, value in encode_dict.items()}

def   __lowercase       (			snake_case			):







				"""simple docstring"""






				__magic_name__		:Tuple   =   ''''''
				for letter in word.lower():
								if letter.isalpha() or letter == " ":
												encoded += encode_dict[letter]
								else:
												raise Exception('''encode() accepts only letters of the alphabet and spaces'''			)
				return encoded

def   __lowercase       (			snake_case			):







				"""simple docstring"""






				if set(snake_case			) - {"A", "B", " "} != set():
								raise Exception('''decode() accepts only \'A\', \'B\' and spaces'''			)
				__magic_name__		:Dict   =   ''''''
				for word in coded.split():
								while len(snake_case			) != 0:
												decoded += decode_dict[word[:5]]
												__magic_name__		:int   =   word[5:]
								decoded += " "
				return decoded.strip()


if __name__ == "__main__":
					from doctest import testmod

					testmod()






