

"""simple docstring"""




import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


_SCREAMING_SNAKE_CASE					:  Optional[int]             =      logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE					:  Any             =      {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
_SCREAMING_SNAKE_CASE					:  str             =      {
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

_SCREAMING_SNAKE_CASE					:  List[str]             =      {
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}






class 	UpperCAmelCase__		(	UpperCamelCase__	):






  """simple docstring"""


  a									= VOCAB_FILES_NAMES
  a									= PRETRAINED_VOCAB_FILES_MAP
  a									= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a									= ["""input_ids""", """attention_mask"""]
  a									= BartTokenizer






  def __init__(							self						:		List[Any]     ,       __lowerCamelCase						:		Union[str, Any]=None     ,       __lowerCamelCase						:		Any=None     ,       __lowerCamelCase						:		Union[str, Any]=None     ,       __lowerCamelCase						:		Union[str, Any]="replace"     ,       __lowerCamelCase						:		int="<s>"     ,       __lowerCamelCase						:		Tuple="</s>"     ,       __lowerCamelCase						:		List[str]="</s>"     ,       __lowerCamelCase						:		Optional[int]="<s>"     ,       __lowerCamelCase						:		Tuple="<unk>"     ,       __lowerCamelCase						:		List[Any]="<pad>"     ,       __lowerCamelCase						:		List[Any]="<mask>"     ,       __lowerCamelCase						:		Union[str, Any]=False     ,       __lowerCamelCase						:		Optional[Any]=True     ,       **__lowerCamelCase						:		Optional[int]     ,       )		->							List[str]:
       super().__init__(
           __a     ,       __a     ,       tokenizer_file=__a     ,       errors=__a     ,       bos_token=__a     ,       eos_token=__a     ,       sep_token=__a     ,       cls_token=__a     ,       unk_token=__a     ,       pad_token=__a     ,       mask_token=__a     ,       add_prefix_space=__a     ,       trim_offsets=__a     ,       **__a     ,       )

       SCREAMING_SNAKE_CASE__   =   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
       if pre_tok_state.get('''add_prefix_space'''     ,       __a ) != add_prefix_space:
            SCREAMING_SNAKE_CASE__   =   getattr(__a     ,       pre_tok_state.pop('''type''' ) )
            SCREAMING_SNAKE_CASE__   =   add_prefix_space
            SCREAMING_SNAKE_CASE__   =   pre_tok_class(**__a )

       SCREAMING_SNAKE_CASE__   =   add_prefix_space

       # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
       SCREAMING_SNAKE_CASE__   =   '''post_processor'''
       SCREAMING_SNAKE_CASE__   =   getattr(self.backend_tokenizer     ,       __a     ,       __a )
       if tokenizer_component_instance:
            SCREAMING_SNAKE_CASE__   =   json.loads(tokenizer_component_instance.__getstate__() )

            # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
            if "sep" in state:
                 SCREAMING_SNAKE_CASE__   =   tuple(state['''sep'''] )
            if "cls" in state:
                 SCREAMING_SNAKE_CASE__   =   tuple(state['''cls'''] )

            SCREAMING_SNAKE_CASE__   =   False

            if state.get('''add_prefix_space'''     ,       __a ) != add_prefix_space:
                 SCREAMING_SNAKE_CASE__   =   add_prefix_space
                 SCREAMING_SNAKE_CASE__   =   True

            if state.get('''trim_offsets'''     ,       __a ) != trim_offsets:
                 SCREAMING_SNAKE_CASE__   =   trim_offsets
                 SCREAMING_SNAKE_CASE__   =   True

            if changes_to_apply:
                 SCREAMING_SNAKE_CASE__   =   getattr(__a     ,       state.pop('''type''' ) )
                 SCREAMING_SNAKE_CASE__   =   component_class(**__a )
                 setattr(self.backend_tokenizer     ,       __a     ,       __a )






  @property
  def 				lowercase_		(							self						:		List[str] )		->							int:
       if self._mask_token is None:
            if self.verbose:
                 logger.error('''Using mask_token, but it is not set yet.''' )
            return None
       return str(self._mask_token )






  @mask_token.setter
  def 				lowercase_		(							self						:		int     ,       __lowerCamelCase						:		List[Any] )		->							int:
       SCREAMING_SNAKE_CASE__   =   AddedToken(__a     ,       lstrip=__a     ,       rstrip=__a ) if isinstance(__a     ,       __a ) else value
       SCREAMING_SNAKE_CASE__   =   value






  def 				lowercase_		(							self						:		List[Any]     ,       *__lowerCamelCase						:		Dict     ,       **__lowerCamelCase						:		Dict )		->							Optional[Any]:
       SCREAMING_SNAKE_CASE__   =   kwargs.get('''is_split_into_words'''     ,       __a )

       if is_split_into_words and not self.add_prefix_space:
            raise ValueError(
                f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
                '''to use it with pretokenized inputs.''' )

       return super()._batch_encode_plus(*__a     ,       **__a )






  def 				lowercase_		(							self						:		Dict     ,       *__lowerCamelCase						:		Tuple     ,       **__lowerCamelCase						:		Dict )		->							Tuple:
       SCREAMING_SNAKE_CASE__   =   kwargs.get('''is_split_into_words'''     ,       __a )

       if is_split_into_words and not self.add_prefix_space:
            raise ValueError(
                f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
                '''to use it with pretokenized inputs.''' )

       return super()._encode_plus(*__a     ,       **__a )






  def 				lowercase_		(							self						:		Dict     ,       __lowerCamelCase						:		str     ,       __lowerCamelCase						:		Optional[str] = None )		->							Tuple:
       SCREAMING_SNAKE_CASE__   =   self._tokenizer.model.save(__a     ,       name=__a )
       return tuple(__a )






  def 				lowercase_		(							self						:		Optional[Any]     ,       __lowerCamelCase						:		Optional[Any]     ,       __lowerCamelCase						:		List[str]=None )		->							List[Any]:
       SCREAMING_SNAKE_CASE__   =   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
       if token_ids_a is None:
            return output

       return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







  def 				lowercase_		(							self						:		List[Any]     ,       __lowerCamelCase						:		List[int]     ,       __lowerCamelCase						:		Optional[List[int]] = None )		->							List[Any]:
       SCREAMING_SNAKE_CASE__   =   [self.sep_token_id]
       SCREAMING_SNAKE_CASE__   =   [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_       (						_A    ):





     '''simple docstring'''




     if divisor % 5 == 0 or divisor % 2 == 0:
          return 0
     SCREAMING_SNAKE_CASE__   =   1
     SCREAMING_SNAKE_CASE__   =   1
     while repunit:
          SCREAMING_SNAKE_CASE__   =   (10 * repunit + 1) % divisor
          repunit_index += 1
     return repunit_index
def     UpperCAmelCase_       (						_A = 1_00_00_00    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   limit - 1
     if divisor % 2 == 0:
          divisor += 1
     while least_divisible_repunit(_A    ) <= limit:
          divisor += 2
     return divisor


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


