

"""simple docstring"""




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

import sentencepiece as spm

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


SCREAMING_SNAKE_CASE_            = logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            = {'vocab_file': 'sentencepiece.model'}

SCREAMING_SNAKE_CASE_            = {
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

SCREAMING_SNAKE_CASE_            = {
    'google/rembert': 256,
}

class 			a					(		__lowercase			):
						_lowercase        =     VOCAB_FILES_NAMES
						_lowercase        =     PRETRAINED_VOCAB_FILES_MAP
						_lowercase        =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


						def __init__(    self  ,   A_  ,   A_=False  ,   A_=True  ,   A_=True  ,   A_="[CLS]"  ,   A_="[SEP]"  ,   A_="[UNK]"  ,   A_="[SEP]"  ,   A_="[PAD]"  ,   A_="[CLS]"  ,   A_="[MASK]"  ,   **A_  ,   ):







										'''simple docstring'''


										super().__init__(
										    do_lower_case=UpperCAmelCase__  ,   remove_space=UpperCAmelCase__  ,   keep_accents=UpperCAmelCase__  ,   bos_token=UpperCAmelCase__  ,   eos_token=UpperCAmelCase__  ,   unk_token=UpperCAmelCase__  ,   sep_token=UpperCAmelCase__  ,   pad_token=UpperCAmelCase__  ,   cls_token=UpperCAmelCase__  ,   mask_token=UpperCAmelCase__  ,   **UpperCAmelCase__  ,   )

										_UpperCAmelCase    :						List[str]							=      do_lower_case
										_UpperCAmelCase    :						Any							=      remove_space
										_UpperCAmelCase    :						Optional[Any]							=      keep_accents
										_UpperCAmelCase    :						Tuple							=      vocab_file

										_UpperCAmelCase    :						str							=      spm.SentencePieceProcessor()
										self.sp_model.Load(UpperCAmelCase__		)


						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return len(self.sp_model		)


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Union[str, Any]							=      {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		):







										'''simple docstring'''


										_UpperCAmelCase    :						Optional[int]							=      self.__dict__.copy()
										_UpperCAmelCase    :						Dict							=      None
										return state


						def __setstate__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[str]							=      d
										_UpperCAmelCase    :						Optional[Any]							=      spm.SentencePieceProcessor()
										self.sp_model.Load(self.vocab_file		)


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_=False		):







										'''simple docstring'''


										_UpperCAmelCase    :						Tuple							=      self.sp_model.EncodeAsPieces(UpperCAmelCase__		)
										return pieces


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										return self.sp_model.PieceToId(UpperCAmelCase__		)


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										return self.sp_model.IdToPiece(UpperCAmelCase__		)


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						Tuple							=      self.sp_model.decode_pieces(UpperCAmelCase__		)
										return out_string


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_ = None		):







										'''simple docstring'''


										_UpperCAmelCase    :						Dict							=      [self.sep_token_id]
										_UpperCAmelCase    :						List[str]							=      [self.cls_token_id]
										if token_ids_a is None:
														return cls + token_ids_a + sep
										return cls + token_ids_a + sep + token_ids_a + sep


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_ = None  ,   A_ = False		):







										'''simple docstring'''


										if already_has_special_tokens:
														if token_ids_a is not None:
																		raise ValueError(
																		    "You should not supply a second sequence if the provided sequence of "
																		    "ids is already formatted with special tokens for the model."		)
														return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

										if token_ids_a is not None:
														return [1] + ([0] * len(UpperCAmelCase__		)) + [1] + ([0] * len(UpperCAmelCase__		)) + [1]
										return [1] + ([0] * len(UpperCAmelCase__		)) + [1]


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_ = None		):







										'''simple docstring'''


										_UpperCAmelCase    :						str							=      [self.sep_token_id]
										_UpperCAmelCase    :						List[str]							=      [self.cls_token_id]

										if token_ids_a is None:
														return len(cls + token_ids_a + sep		) * [0]
										return len(cls + token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1]





						def     _UpperCAmelCase			(    self  ,   A_  ,   A_ = None		):







										'''simple docstring'''


										if not os.path.isdir(UpperCAmelCase__		):
														logger.error("Vocabulary path ({}) should be a directory".format(UpperCAmelCase__		)		)
														return
										_UpperCAmelCase    :						Any							=      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__		):
														copyfile(self.vocab_file  ,   UpperCAmelCase__		)

										return (out_vocab_file,)





def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int	)				->    int:
				if not isinstance(lowerCAmelCase					, lowerCAmelCase	):
								raise TypeError("Input value must be an 'int' type"	)

				_UpperCAmelCase    :						List[Any]							=      0
				while number:
								position += 1
								number >>= 1

				return position


if __name__ == "__main__":
					import doctest

					doctest.testmod()


