'''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_ : int						  =      None


lowerCAmelCase_ : int						  =      logging.get_logger(__name__)


lowerCAmelCase_ : int						  =      {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowerCAmelCase_ : List[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": 1_024,
    "facebook/mbart-large-cc25": 1_024,
}

# fmt: off
lowerCAmelCase_ : Dict						  =      ["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 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					=VOCAB_FILES_NAMES
   lowerCamelCase_    					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_    					=PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_    					=['input_ids', 'attention_mask']
   lowerCamelCase_    					=MBartTokenizer

   lowerCamelCase_    					=[]
   lowerCamelCase_    					=[]


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

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

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

         lowercase_     =      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})
         lowercase_     =      {
             lang_code: self.convert_tokens_to_ids(__lowerCAmelCase) for lang_code in FAIRSEQ_LANGUAGE_CODES
         }

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


   @property
   def __UpperCAmelCase       (   self				:	int)      ->					str:
         return self._src_lang


   @src_lang.setter
   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	str)      ->					None:
         lowercase_     =      new_src_lang
         self.set_src_lang_special_tokens(self._src_lang)


   def __UpperCAmelCase       (   self				:	List[Any]   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = None)      ->					List[int]:
         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 __UpperCAmelCase       (   self				:	Union[str, Any]   ,		__lowerCAmelCase				:	List[int]   ,		__lowerCAmelCase				:	Optional[List[int]] = 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 + sep + token_ids_a + sep) * [0]


   def __UpperCAmelCase       (   self				:	Optional[Any]   ,		__lowerCAmelCase				:	List[Any]   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Optional[str]   ,		__lowerCAmelCase				:	Optional[str]   ,		**__lowerCAmelCase				:	Optional[int])      ->					List[Any]:
         if src_lang is None or tgt_lang is None:
               raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model")
         lowercase_     =      src_lang
         lowercase_     =      self(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase   ,		return_tensors=__lowerCAmelCase   ,		**__lowerCAmelCase)
         lowercase_     =      self.convert_tokens_to_ids(__lowerCAmelCase)
         lowercase_     =      tgt_lang_id
         return inputs


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		__lowerCAmelCase				:	List[str]   ,		__lowerCAmelCase				:	str = "en_XX"   ,		__lowerCAmelCase				:	Optional[List[str]] = None   ,		__lowerCAmelCase				:	str = "ro_RO"   ,		**__lowerCAmelCase				:	Optional[Any]   ,		)      ->					BatchEncoding:
         lowercase_     =      src_lang
         lowercase_     =      tgt_lang
         return super().prepare_seqaseq_batch(__lowerCAmelCase   ,		__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	str)      ->					Optional[int]:
         return self.set_src_lang_special_tokens(self.src_lang)


   def __UpperCAmelCase       (   self				:	Any)      ->					List[Any]:
         return self.set_tgt_lang_special_tokens(self.tgt_lang)


   def __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	Tuple)      ->					None:
         lowercase_     =      self.convert_tokens_to_ids(__lowerCAmelCase)
         lowercase_     =      []
         lowercase_     =      [self.eos_token_id, self.cur_lang_code]

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

         lowercase_     =      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 __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	str)      ->					None:
         lowercase_     =      self.convert_tokens_to_ids(__lowerCAmelCase)
         lowercase_     =      []
         lowercase_     =      [self.eos_token_id, self.cur_lang_code]

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

         lowercase_     =      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 __UpperCAmelCase       (   self				:	str   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Optional[str] = None)      ->					Tuple[str]:
         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(__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):
               copyfile(self.vocab_file   ,		__lowerCAmelCase)

         return (out_vocab_file,)







'''simple docstring'''

from __future__ import annotations


def __a (	__lowerCamelCase			:						int				)	->							list[int]:
      '''simple docstring'''


      lowercase_     =      [True] * limit
      lowercase_     =      False
      lowercase_     =      False
      lowercase_     =      True

      for i in range(3 ,		int(limit**0.5 + 1				) ,		2				):
            lowercase_     =      i * 2
            while index < limit:
                  lowercase_     =      False
                  lowercase_     =      index + i

      lowercase_     =      [2]

      for i in range(3 ,		__lowerCamelCase ,		2				):
            if is_prime[i]:
                  primes.append(__lowerCamelCase				)

      return primes


def __a (	__lowerCamelCase			:						int = 1_000_000				)	->							int:
      '''simple docstring'''


      lowercase_     =      prime_sieve(__lowerCamelCase				)
      lowercase_     =      0
      lowercase_     =      0

      for i in range(len(__lowerCamelCase				)				):
            for j in range(i + length ,		len(__lowerCamelCase				)				):
                  lowercase_     =      sum(primes[i:j]				)
                  if sol >= ceiling:
                        break

                  if sol in primes:
                        lowercase_     =      j - i
                        lowercase_     =      sol

      return largest


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






