



'''simple docstring'''


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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
   from .tokenization_mbart import MBartTokenizer
else:
   _lowerCamelCase	:       Tuple      	=	None


_lowerCamelCase	:       int      	=	logging.get_logger(__name__)


_lowerCamelCase	:       Any      	=	{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

_lowerCamelCase	:       Union[str, Any]      	=	{
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

_lowerCamelCase	:       str      	=	{
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
_lowerCamelCase	:       List[str]      	=	["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN"]

class  SCREAMING_SNAKE_CASE (  _a		):






    """simple docstring"""





    _SCREAMING_SNAKE_CASE	  =  VOCAB_FILES_NAMES
    _SCREAMING_SNAKE_CASE	  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _SCREAMING_SNAKE_CASE	  =  PRETRAINED_VOCAB_FILES_MAP
    _SCREAMING_SNAKE_CASE	  =  ["""input_ids""", """attention_mask"""]
    _SCREAMING_SNAKE_CASE	  =  MBartTokenizer

    _SCREAMING_SNAKE_CASE	  =  []
    _SCREAMING_SNAKE_CASE	  =  []






    def __init__(  self      :					Optional[int]  ,						UpperCamelCase__      :					int=None  ,						UpperCamelCase__      :					Union[str, Any]=None  ,						UpperCamelCase__      :					int="<s>"  ,						UpperCamelCase__      :					str="</s>"  ,						UpperCamelCase__      :					Optional[int]="</s>"  ,						UpperCamelCase__      :					Tuple="<s>"  ,						UpperCamelCase__      :					Optional[Any]="<unk>"  ,						UpperCamelCase__      :					Dict="<pad>"  ,						UpperCamelCase__      :					Optional[Any]="<mask>"  ,						UpperCamelCase__      :					List[str]=None  ,						UpperCamelCase__      :					List[str]=None  ,						UpperCamelCase__      :					Any=None  ,						**UpperCamelCase__      :					Union[str, Any]  ,						):


       """simple docstring"""







       UpperCamelCase					=  AddedToken(UpperCamelCase__  ,						lstrip=UpperCamelCase__  ,						rstrip=UpperCamelCase__ ) if isinstance(UpperCamelCase__  ,						UpperCamelCase__ ) else mask_token

       super().__init__(
           vocab_file=UpperCamelCase__  ,						tokenizer_file=UpperCamelCase__  ,						bos_token=UpperCamelCase__  ,						eos_token=UpperCamelCase__  ,						sep_token=UpperCamelCase__  ,						cls_token=UpperCamelCase__  ,						unk_token=UpperCamelCase__  ,						pad_token=UpperCamelCase__  ,						mask_token=UpperCamelCase__  ,						src_lang=UpperCamelCase__  ,						tgt_lang=UpperCamelCase__  ,						additional_special_tokens=UpperCamelCase__  ,						**UpperCamelCase__  ,						)

       UpperCamelCase					=  vocab_file
       UpperCamelCase					=  False if not self.vocab_file else True

       UpperCamelCase					=  FAIRSEQ_LANGUAGE_CODES.copy()

       if additional_special_tokens is not None:
          # Only add those special tokens if they are not already there.
          _additional_special_tokens.extend(
              [t for t in additional_special_tokens if t not in _additional_special_tokens] )

       self.add_special_tokens({'additional_special_tokens': _additional_special_tokens} )
       UpperCamelCase					=  {
           lang_code: self.convert_tokens_to_ids(UpperCamelCase__ ) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

       UpperCamelCase					=  src_lang if src_lang is not None else 'en_XX'
       UpperCamelCase					=  self.convert_tokens_to_ids(self._src_lang )
       UpperCamelCase					=  tgt_lang
       self.set_src_lang_special_tokens(self._src_lang )






    @property
    def  A       (  self      :					str ):


       """simple docstring"""







       return self._src_lang






    @src_lang.setter
    def  A       (  self      :					Optional[Any]  ,						UpperCamelCase__      :					str ):


       """simple docstring"""







       UpperCamelCase					=  new_src_lang
       self.set_src_lang_special_tokens(self._src_lang )






    def  A       (  self      :					Dict  ,						UpperCamelCase__      :					List[int]  ,						UpperCamelCase__      :					Optional[List[int]] = None ):


       """simple docstring"""







       if token_ids_a is None:
          return self.prefix_tokens + token_ids_a + self.suffix_tokens
       # We don't expect to process pairs, but leave the pair logic for API consistency
       return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens






    def  A       (  self      :					List[Any]  ,						UpperCamelCase__      :					List[int]  ,						UpperCamelCase__      :					Optional[List[int]] = None ):


       """simple docstring"""







       UpperCamelCase					=  [self.sep_token_id]
       UpperCamelCase					=  [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]






    def  A       (  self      :					List[str]  ,						UpperCamelCase__      :					str  ,						UpperCamelCase__      :					str  ,						UpperCamelCase__      :					Optional[str]  ,						UpperCamelCase__      :					Optional[str]  ,						**UpperCamelCase__      :					int ):


       """simple docstring"""







       if src_lang is None or tgt_lang is None:
          raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model' )
       UpperCamelCase					=  src_lang
       UpperCamelCase					=  self(UpperCamelCase__  ,						add_special_tokens=UpperCamelCase__  ,						return_tensors=UpperCamelCase__  ,						**UpperCamelCase__ )
       UpperCamelCase					=  self.convert_tokens_to_ids(UpperCamelCase__ )
       UpperCamelCase					=  tgt_lang_id
       return inputs






    def  A       (  self      :					str  ,						UpperCamelCase__      :					List[str]  ,						UpperCamelCase__      :					str = "en_XX"  ,						UpperCamelCase__      :					Optional[List[str]] = None  ,						UpperCamelCase__      :					str = "ro_RO"  ,						**UpperCamelCase__      :					int  ,						):


       """simple docstring"""







       UpperCamelCase					=  src_lang
       UpperCamelCase					=  tgt_lang
       return super().prepare_seqaseq_batch(UpperCamelCase__  ,						UpperCamelCase__  ,						**UpperCamelCase__ )






    def  A       (  self      :					int ):


       """simple docstring"""







       return self.set_src_lang_special_tokens(self.src_lang )






    def  A       (  self      :					Union[str, Any] ):


       """simple docstring"""







       return self.set_tgt_lang_special_tokens(self.tgt_lang )






    def  A       (  self      :					Tuple  ,						UpperCamelCase__      :					Any ):


       """simple docstring"""







       UpperCamelCase					=  self.convert_tokens_to_ids(UpperCamelCase__ )
       UpperCamelCase					=  []
       UpperCamelCase					=  [self.eos_token_id, self.cur_lang_code]

       UpperCamelCase					=  self.convert_ids_to_tokens(self.prefix_tokens )
       UpperCamelCase					=  self.convert_ids_to_tokens(self.suffix_tokens )

       UpperCamelCase					=  processors.TemplateProcessing(
           single=prefix_tokens_str + ['$A'] + suffix_tokens_str  ,						pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str  ,						special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,						self.prefix_tokens + self.suffix_tokens ) )  ,						)






    def  A       (  self      :					List[str]  ,						UpperCamelCase__      :					str ):


       """simple docstring"""







       UpperCamelCase					=  self.convert_tokens_to_ids(UpperCamelCase__ )
       UpperCamelCase					=  []
       UpperCamelCase					=  [self.eos_token_id, self.cur_lang_code]

       UpperCamelCase					=  self.convert_ids_to_tokens(self.prefix_tokens )
       UpperCamelCase					=  self.convert_ids_to_tokens(self.suffix_tokens )

       UpperCamelCase					=  processors.TemplateProcessing(
           single=prefix_tokens_str + ['$A'] + suffix_tokens_str  ,						pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str  ,						special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,						self.prefix_tokens + self.suffix_tokens ) )  ,						)






    def  A       (  self      :					Optional[int]  ,						UpperCamelCase__      :					str  ,						UpperCamelCase__      :					Optional[str] = None ):


       """simple docstring"""







       if not self.can_save_slow_tokenizer:
          raise ValueError(
              'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
              'tokenizer.' )

       if not os.path.isdir(UpperCamelCase__ ):
          logger.error(f"""Vocabulary path ({save_directory}) should be a directory.""" )
          return
       UpperCamelCase					=  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,)






'''simple docstring'''


def 				__lowerCamelCase				(   A__ = 10**9    )       ->	int:






   """simple docstring"""
   UpperCamelCase					=  1
   UpperCamelCase					=  2

   UpperCamelCase					=  0
   UpperCamelCase					=  0
   UpperCamelCase					=  0
   while perimeter <= max_perimeter:
      perimeters_sum += perimeter

      prev_value += 2 * value
      value += prev_value

      UpperCamelCase					=  2 * value + 2 if i % 2 == 0 else 2 * value - 2
      i += 1

   return perimeters_sum


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

