



'''simple docstring'''





import os
import re
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


SCREAMING_SNAKE_CASE__      					=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__      					=     {"vocab_file": "spiece.model"}

SCREAMING_SNAKE_CASE__      					=     {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

SCREAMING_SNAKE_CASE__      					=     {
    "google/bigbird-roberta-base": 4096,
    "google/bigbird-roberta-large": 4096,
    "google/bigbird-base-trivia-itc": 4096,
}


class 				snake_case (__a   ):
       lowerCAmelCase__  :int						   =					VOCAB_FILES_NAMES
       lowerCAmelCase__  :Any						   =					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__  :Dict						   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__  :int						   =					["input_ids", "attention_mask"]
       lowerCAmelCase__  :List[int]						   =					[]



       def __init__(				self     ,UpperCAmelCase_     ,UpperCAmelCase_="<unk>"     ,UpperCAmelCase_="<s>"     ,UpperCAmelCase_="</s>"     ,UpperCAmelCase_="<pad>"     ,UpperCAmelCase_="[SEP]"     ,UpperCAmelCase_="[MASK]"     ,UpperCAmelCase_="[CLS]"     ,UpperCAmelCase_ = None     ,**UpperCAmelCase_     ,)  ->							None:
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else bos_token
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else eos_token
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else unk_token
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else pad_token
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else cls_token
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else sep_token

           # Mask token behave like a normal word, i.e. include the space before it
           lowercase__		       =						AddedToken(lowerCAmelCase_     ,lstrip=lowerCAmelCase_     ,rstrip=lowerCAmelCase_      ) if isinstance(lowerCAmelCase_     ,lowerCAmelCase_      ) else mask_token

           lowercase__		       =						{} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               bos_token=lowerCAmelCase_     ,eos_token=lowerCAmelCase_     ,unk_token=lowerCAmelCase_     ,pad_token=lowerCAmelCase_     ,sep_token=lowerCAmelCase_     ,mask_token=lowerCAmelCase_     ,cls_token=lowerCAmelCase_     ,sp_model_kwargs=self.sp_model_kwargs     ,**lowerCAmelCase_     ,)

           lowercase__		       =						vocab_file

           lowercase__		       =						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
           self.sp_model.Load(lowerCAmelCase_      )



       @property
       def 							_a      (				self      )  ->							List[Any]:
           return self.sp_model.get_piece_size()



       def 							_a      (				self      )  ->							Optional[Any]:
           lowercase__		       =						{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      )  ->							Optional[Any]:
           lowercase__		       =						self.__dict__.copy()
           lowercase__		       =						None
           return state



       def __setstate__(				self     ,UpperCAmelCase_      )  ->							List[Any]:
           lowercase__		       =						d

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

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



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



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Any:
           return self.sp_model.piece_to_id(lowerCAmelCase_      )



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Optional[Any]:
           lowercase__		       =						self.sp_model.IdToPiece(lowerCAmelCase_      )
           return token



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Union[str, Any]:
           lowercase__		       =						[]
           lowercase__		       =						""
           lowercase__		       =						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
                   lowercase__		       =						True
                   lowercase__		       =						[]
               else:
                   current_sub_tokens.append(lowerCAmelCase_      )
                   lowercase__		       =						False
           out_string += self.sp_model.decode(lowerCAmelCase_      )
           return out_string.strip()



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = False     ,UpperCAmelCase_ = None     ,UpperCAmelCase_ = True     ,**UpperCAmelCase_     ,)  ->							str:
           lowercase__		       =						kwargs.pop("use_source_tokenizer"     ,lowerCAmelCase_      )

           lowercase__		       =						self.convert_ids_to_tokens(lowerCAmelCase_     ,skip_special_tokens=lowerCAmelCase_      )

           # To avoid mixing byte-level and unicode for byte-level BPT
           # we need to build string separately for added tokens and byte-level tokens
           # cf. https://github.com/huggingface/transformers/issues/1133
           lowercase__		       =						[]
           lowercase__		       =						[]
           for token in filtered_tokens:
               if skip_special_tokens and token in self.all_special_ids:
                   continue
               if token in self.added_tokens_encoder:
                   if current_sub_text:
                       sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase_      )      )
                       lowercase__		       =						[]
                   sub_texts.append(lowerCAmelCase_      )
               else:
                   current_sub_text.append(lowerCAmelCase_      )
           if current_sub_text:
               sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase_      )      )

           # Mimic the behavior of the Rust tokenizer:
           # No space before [MASK] and [SEP]
           if spaces_between_special_tokens:
               lowercase__		       =						re.sub(R" (\[(MASK|SEP)\])"     ,R"\1"     ," ".join(lowerCAmelCase_      )      )
           else:
               lowercase__		       =						"".join(lowerCAmelCase_      )

           lowercase__		       =						(
               clean_up_tokenization_spaces
               if clean_up_tokenization_spaces is not None
               else self.clean_up_tokenization_spaces
           )
           if clean_up_tokenization_spaces:
               lowercase__		       =						self.clean_up_tokenization(lowerCAmelCase_      )
               return clean_text
           else:
               return text



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							Tuple[str]:







           if not os.path.isdir(lowerCAmelCase_      ):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
               return
           lowercase__		       =						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:
                   lowercase__		       =						self.sp_model.serialized_model_proto()
                   fi.write(lowerCAmelCase_      )

           return (out_vocab_file,)



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							List[int]:







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



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None     ,UpperCAmelCase_ = False      )  ->							List[int]:







           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] + ([0] * len(lowerCAmelCase_      )) + [1]







       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							List[int]:
           lowercase__		       =						[self.sep_token_id]
           lowercase__		       =						[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]









'''simple docstring'''





def        lowerCamelCase  (				_snake_case  :						int = 4_000_000       ):





    '''simple docstring'''


    lowercase__		       =						[0, 1]
    lowercase__		       =						0
    while fib[i] <= n:
        fib.append(fib[i] + fib[i + 1]       )
        if fib[i + 2] > n:
            break
        i += 1
    lowercase__		       =						0
    for j in range(len(_snake_case       ) - 1       ):
        if fib[j] % 2 == 0:
            total += fib[j]

    return total


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




