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			:						int				  =		logging.get_logger(__name__)


SCREAMING_SNAKE_CASE			:						Optional[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			:						Union[str, Any]				  =		{
    """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			:						int				  =		{
    """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  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      VOCAB_FILES_NAMES
  _SCREAMING_SNAKE_CASE     					=      PRETRAINED_VOCAB_FILES_MAP
  _SCREAMING_SNAKE_CASE     					=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _SCREAMING_SNAKE_CASE     					=      ["""input_ids""", """attention_mask"""]
  _SCREAMING_SNAKE_CASE     					=      BartTokenizer

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

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

   __a							=	add_prefix_space

   # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
   __a							=	"post_processor"
   __a							=	getattr(self.backend_tokenizer  ,				__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							)
   if tokenizer_component_instance:
    __a							=	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:
     __a							=	tuple(state["sep"]							)
    if "cls" in state:
     __a							=	tuple(state["cls"]							)

    __a							=	False

    if state.get("add_prefix_space"  ,				__SCREAMING_SNAKE_CASE							) != add_prefix_space:
     __a							=	add_prefix_space
     __a							=	True

    if state.get("trim_offsets"  ,				__SCREAMING_SNAKE_CASE							) != trim_offsets:
     __a							=	trim_offsets
     __a							=	True

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

  @property
  def 		_UpperCAmelCase (		self			:   Dict							):
   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 		_UpperCAmelCase (		self			:   Optional[int]  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]							):
   __a							=	AddedToken(__SCREAMING_SNAKE_CASE  ,				lstrip=__SCREAMING_SNAKE_CASE  ,				rstrip=__SCREAMING_SNAKE_CASE							) if isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							) else value
   __a							=	value

  def 		_UpperCAmelCase (		self			:   Optional[int]  ,				*__SCREAMING_SNAKE_CASE			:   Optional[int]  ,				**__SCREAMING_SNAKE_CASE			:   List[str]							):
   __a							=	kwargs.get("is_split_into_words"  ,				__SCREAMING_SNAKE_CASE							)

   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(*__SCREAMING_SNAKE_CASE  ,				**__SCREAMING_SNAKE_CASE							)

  def 		_UpperCAmelCase (		self			:   List[str]  ,				*__SCREAMING_SNAKE_CASE			:   Optional[Any]  ,				**__SCREAMING_SNAKE_CASE			:   int							):
   __a							=	kwargs.get("is_split_into_words"  ,				__SCREAMING_SNAKE_CASE							)

   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(*__SCREAMING_SNAKE_CASE  ,				**__SCREAMING_SNAKE_CASE							)

  def 		_UpperCAmelCase (		self			:   Tuple  ,				__SCREAMING_SNAKE_CASE			:   str  ,				__SCREAMING_SNAKE_CASE			:   Optional[str] = None							):
   __a							=	self._tokenizer.model.save(__SCREAMING_SNAKE_CASE  ,				name=__SCREAMING_SNAKE_CASE							)
   return tuple(__SCREAMING_SNAKE_CASE							)

  def 		_UpperCAmelCase (		self			:   List[str]  ,				__SCREAMING_SNAKE_CASE			:   Optional[int]  ,				__SCREAMING_SNAKE_CASE			:   List[str]=None							):
   __a							=	[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 		_UpperCAmelCase (		self			:   str  ,				__SCREAMING_SNAKE_CASE			:   List[int]  ,				__SCREAMING_SNAKE_CASE			:   Optional[List[int]] = None							):
   __a							=	[self.sep_token_id]
   __a							=	[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		(      _A				,					_A       ):



 """simple docstring"""


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



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


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



def 	__A		(      _A = 20       ):



 """simple docstring"""


 __a							=	1
 for i in range(1				,					n + 1       ):
  __a							=	lcm(_A				,					_A       )
 return g


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


