





"""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': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# 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 		__snake_case					(		UpperCamelCase__     ):





 """simple docstring"""


 _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					,						__lowerCamelCase=None					,						__lowerCamelCase=None					,						__lowerCamelCase="<s>"					,						__lowerCamelCase="</s>"					,						__lowerCamelCase="</s>"					,						__lowerCamelCase="<s>"					,						__lowerCamelCase="<unk>"					,						__lowerCamelCase="<pad>"					,						__lowerCamelCase="<mask>"					,						__lowerCamelCase=None					,						__lowerCamelCase=None					,						__lowerCamelCase=None					,						**__lowerCamelCase					,						):



     '''simple docstring'''




     __A    :						Optional[Any]						 =     AddedToken(__a					,						lstrip=__a					,						rstrip=__a  ) if isinstance(__a					,						__a  ) else mask_token

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

     __A    :						Union[str, Any]						 =     vocab_file
     __A    :						Optional[Any]						 =     False if not self.vocab_file else True

     __A    :						Any						 =     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}  )
     __A    :						Optional[Any]						 =     {
         lang_code: self.convert_tokens_to_ids(__a  ) for lang_code in FAIRSEQ_LANGUAGE_CODES
     }

     __A    :						List[Any]						 =     src_lang if src_lang is not None else '''en_XX'''
     __A    :						Union[str, Any]						 =     self.convert_tokens_to_ids(self._src_lang  )
     __A    :						Union[str, Any]						 =     tgt_lang
     self.set_src_lang_special_tokens(self._src_lang  )

 @property
 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     return self._src_lang

 @src_lang.setter
 def 					UpperCamelCase__(    self					,						__lowerCamelCase  ):



     '''simple docstring'''




     __A    :						Dict						 =     new_src_lang
     self.set_src_lang_special_tokens(self._src_lang  )

 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						__lowerCamelCase = 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 					UpperCamelCase__(    self					,						__lowerCamelCase					,						__lowerCamelCase = None  ):



     '''simple docstring'''




     __A    :						Dict						 =     [self.sep_token_id]
     __A    :						List[str]						 =     [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					,						__lowerCamelCase					,						__lowerCamelCase					,						__lowerCamelCase					,						__lowerCamelCase					,						**__lowerCamelCase  ):



     '''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'''  )
     __A    :						Any						 =     src_lang
     __A    :						int						 =     self(__a					,						add_special_tokens=__a					,						return_tensors=__a					,						**__a  )
     __A    :						int						 =     self.convert_tokens_to_ids(__a  )
     __A    :						int						 =     tgt_lang_id
     return inputs

 def 					UpperCamelCase__(    self					,						__lowerCamelCase					,						__lowerCamelCase = "en_XX"					,						__lowerCamelCase = None					,						__lowerCamelCase = "ro_RO"					,						**__lowerCamelCase					,						):



     '''simple docstring'''




     __A    :						int						 =     src_lang
     __A    :						Dict						 =     tgt_lang
     return super().prepare_seqaseq_batch(__a					,						__a					,						**__a  )

 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     return self.set_src_lang_special_tokens(self.src_lang  )

 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     return self.set_tgt_lang_special_tokens(self.tgt_lang  )

 def 					UpperCamelCase__(    self					,						__lowerCamelCase  ):



     '''simple docstring'''




     __A    :						Optional[Any]						 =     self.convert_tokens_to_ids(__a  )
     __A    :						List[Any]						 =     []
     __A    :						Optional[Any]						 =     [self.eos_token_id, self.cur_lang_code]

     __A    :						Dict						 =     self.convert_ids_to_tokens(self.prefix_tokens  )
     __A    :						List[Any]						 =     self.convert_ids_to_tokens(self.suffix_tokens  )

     __A    :						Union[str, Any]						 =     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					,						__lowerCamelCase  ):



     '''simple docstring'''




     __A    :						Optional[int]						 =     self.convert_tokens_to_ids(__a  )
     __A    :						Optional[int]						 =     []
     __A    :						Optional[int]						 =     [self.eos_token_id, self.cur_lang_code]

     __A    :						List[str]						 =     self.convert_ids_to_tokens(self.prefix_tokens  )
     __A    :						Optional[Any]						 =     self.convert_ids_to_tokens(self.suffix_tokens  )

     __A    :						List[str]						 =     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					,						__lowerCamelCase					,						__lowerCamelCase = 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(__a  ):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""  )
         return
     __A    :						List[Any]						 =     os.path.join(
         __a					,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

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

     return (out_vocab_file,)





'''simple docstring'''





def 	lowerCAmelCase_				(					snake_case_       : int					,    snake_case_       : int			)    ->      int:


     '''simple docstring'''




     return x if y == 0 else greatest_common_divisor(snake_case_					,    x % y			)





def 	lowerCAmelCase_				(					snake_case_       : int					,    snake_case_       : int			)    ->      int:


     '''simple docstring'''




     return (x * y) // greatest_common_divisor(snake_case_					,    snake_case_			)





def 	lowerCAmelCase_				(					snake_case_       : int = 20			)    ->      int:


     '''simple docstring'''




     UpperCAmelCase_           =   1
     for i in range(1					,    n + 1			):
          UpperCAmelCase_           =   lcm(snake_case_					,    snake_case_			)
     return g


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




