




'''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:
   A									=None


A									=logging.get_logger(__name__)


A									={'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

A									={
    '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',
    },
}

A									={
    'facebook/mbart-large-en-ro': 10_24,
    'facebook/mbart-large-cc25': 10_24,
}

# fmt: off
A									=['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     _a						(			__a				):
       __a       :  Optional[Any]            =      VOCAB_FILES_NAMES
       __a       :  List[Any]            =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __a       :  Any            =      PRETRAINED_VOCAB_FILES_MAP
       __a       :  Optional[Any]            =      ["""input_ids""", """attention_mask"""]
       __a       :  List[Any]            =      MBartTokenizer

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



           '''simple docstring'''

           UpperCAmelCase     =	AddedToken(lowercase     ,       lstrip=lowercase     ,       rstrip=lowercase       ) if isinstance(lowercase     ,       lowercase       ) else mask_token

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

           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(lowercase       ) 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		:			Dict       ):



           '''simple docstring'''

           return self._src_lang
       @src_lang.setter
       def 					A   (			self		:			Tuple     ,       lowercase		:			str       ):



           '''simple docstring'''

           UpperCAmelCase     =	new_src_lang
           self.set_src_lang_special_tokens(self._src_lang       )
       def 					A   (			self		:			Dict     ,       lowercase		:			List[int]     ,       lowercase		:			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		:			Optional[Any]     ,       lowercase		:			List[int]     ,       lowercase		:			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		:			Any     ,       lowercase		:			Union[str, Any]     ,       lowercase		:			str     ,       lowercase		:			Optional[str]     ,       lowercase		:			Optional[str]     ,       **lowercase		:			Optional[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(lowercase     ,       add_special_tokens=lowercase     ,       return_tensors=lowercase     ,       **lowercase       )
           UpperCAmelCase     =	self.convert_tokens_to_ids(lowercase       )
           UpperCAmelCase     =	tgt_lang_id
           return inputs
       def 					A   (			self		:			Tuple     ,       lowercase		:			List[str]     ,       lowercase		:			str = "en_XX"     ,       lowercase		:			Optional[List[str]] = None     ,       lowercase		:			str = "ro_RO"     ,       **lowercase		:			str     ,       ):



           '''simple docstring'''

           UpperCAmelCase     =	src_lang
           UpperCAmelCase     =	tgt_lang
           return super().prepare_seqaseq_batch(lowercase     ,       lowercase     ,       **lowercase       )
       def 					A   (			self		:			Optional[Any]       ):



           '''simple docstring'''

           return self.set_src_lang_special_tokens(self.src_lang       )
       def 					A   (			self		:			int       ):



           '''simple docstring'''

           return self.set_tgt_lang_special_tokens(self.tgt_lang       )
       def 					A   (			self		:			int     ,       lowercase		:			Tuple       ):



           '''simple docstring'''

           UpperCAmelCase     =	self.convert_tokens_to_ids(lowercase       )
           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]     ,       lowercase		:			str       ):



           '''simple docstring'''

           UpperCAmelCase     =	self.convert_tokens_to_ids(lowercase       )
           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]     ,       lowercase		:			str     ,       lowercase		:			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(lowercase       ):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory."       )
               return
           UpperCAmelCase     =	os.path.join(
               lowercase     ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']       )

           if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowercase       ):
               copyfile(self.vocab_file     ,       lowercase       )

           return (out_vocab_file,)










'''simple docstring'''







def 		snake_case_							():
    for n in range(1					,     1_0_0_0_0_0_0  ):
        yield n * (n + 1) // 2





def 		snake_case_							(_a			:							Union[str, Any]  ):
    UpperCAmelCase     =	1
    UpperCAmelCase     =	2
    while i * i <= n:
        UpperCAmelCase     =	0
        while n % i == 0:
            n //= i
            multiplicity += 1
        divisors_count *= multiplicity + 1
        i += 1
    if n > 1:
        divisors_count *= 2
    return divisors_count





def 		snake_case_							():
    return next(i for i in triangle_number_generator() if count_divisors(_a  ) > 5_0_0  )


if __name__ == "__main__":
   print(solution())




