


'''simple docstring'''



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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__A		=logging.get_logger(__name__)

__A		={'vocab_file': 'sentencepiece.bpe.model'}

__A		={
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    }
}

__A		={
    'camembert-base': 5_12,
}

__A		='▁'


class 						_snake_case   (       a__		):
     lowerCAmelCase :str						=   VOCAB_FILES_NAMES
     lowerCAmelCase :Optional[Any]						=   PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase :Any						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase :str						=   ['''input_ids''', '''attention_mask''']




     def __init__( self							,							_lowerCamelCase							,							_lowerCamelCase="<s>"							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="<s>"							,							_lowerCamelCase="<unk>"							,							_lowerCamelCase="<pad>"							,							_lowerCamelCase="<mask>"							,							_lowerCamelCase=["<s>NOTUSED", "</s>NOTUSED"]							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
        # Mask token behave like a normal word, i.e. include the space before it
        UpperCAmelCase__					:   Tuple       				=       AddedToken(_lowerCamelCase							,							lstrip=_lowerCamelCase							,							rstrip=_lowerCamelCase) if isinstance(_lowerCamelCase							,							_lowerCamelCase) else mask_token

        UpperCAmelCase__					:   Dict       				=       {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=_lowerCamelCase							,							eos_token=_lowerCamelCase							,							unk_token=_lowerCamelCase							,							sep_token=_lowerCamelCase							,							cls_token=_lowerCamelCase							,							pad_token=_lowerCamelCase							,							mask_token=_lowerCamelCase							,							additional_special_tokens=_lowerCamelCase							,							sp_model_kwargs=self.sp_model_kwargs							,							**_lowerCamelCase							,							)
        UpperCAmelCase__					:   Optional[int]       				=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
        self.sp_model.Load(str(_lowerCamelCase))
        UpperCAmelCase__					:   Optional[Any]       				=       vocab_file
        # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
        # sentencepiece vocabulary (this is the case for <s> and </s>
        UpperCAmelCase__					:   str       				=       {"""<s>NOTUSED""": 0, """<pad>""": 1, """</s>NOTUSED""": 2, """<unk>""": 3}
        UpperCAmelCase__					:   Tuple       				=       len(self.fairseq_tokens_to_ids)
        UpperCAmelCase__					:   Any       				=       len(self.sp_model) + len(self.fairseq_tokens_to_ids)
        UpperCAmelCase__					:   List[Any]       				=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}




     def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None):

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




     def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None							,							_lowerCamelCase = False):
        if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=_lowerCamelCase							,							token_ids_a=_lowerCamelCase							,							already_has_special_tokens=_lowerCamelCase)

        if token_ids_a is None:
           return [1] + ([0] * len(_lowerCamelCase)) + [1]
        return [1] + ([0] * len(_lowerCamelCase)) + [1, 1] + ([0] * len(_lowerCamelCase)) + [1]




     def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None):
        UpperCAmelCase__					:   Tuple       				=       [self.sep_token_id]
        UpperCAmelCase__					:   Union[str, Any]       				=       [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 + sep + token_ids_a + sep) * [0]




     @property
     def 			snake_case__  ( self):
        return len(self.fairseq_tokens_to_ids) + len(self.sp_model)




     def 			snake_case__  ( self):
        UpperCAmelCase__					:   Dict       				=       {self.convert_ids_to_tokens(_lowerCamelCase): i for i in range(self.vocab_size)}
        vocab.update(self.added_tokens_encoder)
        return vocab




     def 			snake_case__  ( self							,							_lowerCamelCase):
        return self.sp_model.encode(_lowerCamelCase							,							out_type=_lowerCamelCase)




     def 			snake_case__  ( self							,							_lowerCamelCase):
        if token in self.fairseq_tokens_to_ids:
           return self.fairseq_tokens_to_ids[token]
        elif self.sp_model.PieceToId(_lowerCamelCase) == 0:
           # Convert sentence piece unk token to fairseq unk token index
           return self.unk_token_id
        return self.fairseq_offset + self.sp_model.PieceToId(_lowerCamelCase)




     def 			snake_case__  ( self							,							_lowerCamelCase):
        if index in self.fairseq_ids_to_tokens:
           return self.fairseq_ids_to_tokens[index]
        return self.sp_model.IdToPiece(index - self.fairseq_offset)




     def 			snake_case__  ( self							,							_lowerCamelCase):
        UpperCAmelCase__					:   List[str]       				=       []
        UpperCAmelCase__					:   Optional[Any]       				=       """"""
        UpperCAmelCase__					:   Optional[Any]       				=       False
        for token in tokens:
           # make sure that special tokens are not decoded using sentencepiece model
           if token in self.all_special_tokens:
              if not prev_is_special:
                 out_string += " "
              out_string += self.sp_model.decode(_lowerCamelCase) + token
              UpperCAmelCase__					:   List[Any]       				=       True
              UpperCAmelCase__					:   Tuple       				=       []
           else:
              current_sub_tokens.append(_lowerCamelCase)
              UpperCAmelCase__					:   Union[str, Any]       				=       False
        out_string += self.sp_model.decode(_lowerCamelCase)
        return out_string.strip()




     def __getstate__( self):
        UpperCAmelCase__					:   Optional[Any]       				=       self.__dict__.copy()
        UpperCAmelCase__					:   List[str]       				=       None
        return state




     def __setstate__( self							,							_lowerCamelCase):
        UpperCAmelCase__					:   List[str]       				=       d

        # for backward compatibility
        if not hasattr(self							,							"""sp_model_kwargs"""):
           UpperCAmelCase__					:   Tuple       				=       {}

        UpperCAmelCase__					:   str       				=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
        self.sp_model.Load(self.vocab_file)




     def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None):
        if not os.path.isdir(_lowerCamelCase):
           logger.error(f'''Vocabulary path ({save_directory}) should be a directory''')
           return
        UpperCAmelCase__					:   Any       				=       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:
              UpperCAmelCase__					:   Union[str, Any]       				=       self.sp_model.serialized_model_proto()
              fi.write(_lowerCamelCase)

        return (out_vocab_file,)



'''simple docstring'''



def       _UpperCamelCase (						UpperCamelCase__ = 4_0_0_0_0_0_0   ):
			UpperCAmelCase__					:   List[str]       				=       [0, 1]
			UpperCAmelCase__					:   Any       				=       0
			while fib[i] <= n:
						fib.append(fib[i] + fib[i + 1]   )
						if fib[i + 2] > n:
									break
						i += 1
			UpperCAmelCase__					:   str       				=       0
			for j in range(len(UpperCamelCase__   ) - 1   ):
						if fib[j] % 2 == 0:
									total += fib[j]

			return total


if __name__ == "__main__":
		print(f"""{solution() = }""")