





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


__A							   =							logging.get_logger(__name__)


__A							   =							{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all BART models at https://huggingface.co/models?filter=bart
__A							   =							{
    "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",
    },
}

__A							   =							{
    "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   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''
 lowercase_						=     VOCAB_FILES_NAMES
 lowercase_						=     PRETRAINED_VOCAB_FILES_MAP
 lowercase_						=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_						=     ["input_ids", "attention_mask"]
 lowercase_						=     BartTokenizer

 def __init__(self							:  List[Any]			,					UpperCAmelCase_							:  List[Any]=None			,					UpperCAmelCase_							:  str=None			,					UpperCAmelCase_							:  List[str]=None			,					UpperCAmelCase_							:  List[str]="replace"			,					UpperCAmelCase_							:  List[Any]="<s>"			,					UpperCAmelCase_							:  Dict="</s>"			,					UpperCAmelCase_							:  Optional[Any]="</s>"			,					UpperCAmelCase_							:  List[str]="<s>"			,					UpperCAmelCase_							:  List[Any]="<unk>"			,					UpperCAmelCase_							:  Any="<pad>"			,					UpperCAmelCase_							:  Optional[Any]="<mask>"			,					UpperCAmelCase_							:  List[Any]=False			,					UpperCAmelCase_							:  Union[str, Any]=True			,					**UpperCAmelCase_							:  Dict			,					)			->Optional[int]:



   '''simple docstring'''



   super().__init__(
       UpperCAmelCase_			,					UpperCAmelCase_			,					tokenizer_file=UpperCAmelCase_			,					errors=UpperCAmelCase_			,					bos_token=UpperCAmelCase_			,					eos_token=UpperCAmelCase_			,					sep_token=UpperCAmelCase_			,					cls_token=UpperCAmelCase_			,					unk_token=UpperCAmelCase_			,					pad_token=UpperCAmelCase_			,					mask_token=UpperCAmelCase_			,					add_prefix_space=UpperCAmelCase_			,					trim_offsets=UpperCAmelCase_			,					**UpperCAmelCase_			,					)

   lowerCamelCase__: List[str]         =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
   if pre_tok_state.get("add_prefix_space"			,					UpperCAmelCase_) != add_prefix_space:
     lowerCamelCase__: Dict         =getattr(UpperCAmelCase_			,					pre_tok_state.pop("type"))
     lowerCamelCase__: str         =add_prefix_space
     lowerCamelCase__: Optional[Any]         =pre_tok_class(**UpperCAmelCase_)

   lowerCamelCase__: str         =add_prefix_space

   # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
   lowerCamelCase__: Dict         ="post_processor"
   lowerCamelCase__: Optional[Any]         =getattr(self.backend_tokenizer			,					UpperCAmelCase_			,					UpperCAmelCase_)
   if tokenizer_component_instance:
     lowerCamelCase__: List[str]         =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:
       lowerCamelCase__: Optional[Any]         =tuple(state["sep"])
     if "cls" in state:
       lowerCamelCase__: List[Any]         =tuple(state["cls"])

     lowerCamelCase__: List[Any]         =False

     if state.get("add_prefix_space"			,					UpperCAmelCase_) != add_prefix_space:
       lowerCamelCase__: Optional[int]         =add_prefix_space
       lowerCamelCase__: Optional[int]         =True

     if state.get("trim_offsets"			,					UpperCAmelCase_) != trim_offsets:
       lowerCamelCase__: Union[str, Any]         =trim_offsets
       lowerCamelCase__: Optional[Any]         =True

     if changes_to_apply:
       lowerCamelCase__: Dict         =getattr(UpperCAmelCase_			,					state.pop("type"))
       lowerCamelCase__: Any         =component_class(**UpperCAmelCase_)
       setattr(self.backend_tokenizer			,					UpperCAmelCase_			,					UpperCAmelCase_)

 @property
 def 				SCREAMING_SNAKE_CASE_   (self							:  int)			->str:



   '''simple docstring'''



   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 				SCREAMING_SNAKE_CASE_   (self							:  Dict			,					UpperCAmelCase_							:  int)			->Optional[Any]:



   '''simple docstring'''



   lowerCamelCase__: Union[str, Any]         =AddedToken(UpperCAmelCase_			,					lstrip=UpperCAmelCase_			,					rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_			,					UpperCAmelCase_) else value
   lowerCamelCase__: str         =value

 def 				SCREAMING_SNAKE_CASE_   (self							:  Tuple			,					*UpperCAmelCase_							:  Union[str, Any]			,					**UpperCAmelCase_							:  Optional[Any])			->BatchEncoding:



   '''simple docstring'''



   lowerCamelCase__: Any         =kwargs.get("is_split_into_words"			,					UpperCAmelCase_)

   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(*UpperCAmelCase_			,					**UpperCAmelCase_)

 def 				SCREAMING_SNAKE_CASE_   (self							:  List[str]			,					*UpperCAmelCase_							:  Any			,					**UpperCAmelCase_							:  Optional[Any])			->BatchEncoding:



   '''simple docstring'''



   lowerCamelCase__: str         =kwargs.get("is_split_into_words"			,					UpperCAmelCase_)

   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(*UpperCAmelCase_			,					**UpperCAmelCase_)

 def 				SCREAMING_SNAKE_CASE_   (self							:  Dict			,					UpperCAmelCase_							:  str			,					UpperCAmelCase_							:  Optional[str] = None)			->Tuple[str]:



   '''simple docstring'''



   lowerCamelCase__: Optional[int]         =self._tokenizer.model.save(UpperCAmelCase_			,					name=UpperCAmelCase_)
   return tuple(UpperCAmelCase_)

 def 				SCREAMING_SNAKE_CASE_   (self							:  int			,					UpperCAmelCase_							:  Union[str, Any]			,					UpperCAmelCase_							:  List[Any]=None)			->str:



   '''simple docstring'''



   lowerCamelCase__: str         =[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 				SCREAMING_SNAKE_CASE_   (self							:  List[str]			,					UpperCAmelCase_							:  List[int]			,					UpperCAmelCase_							:  Optional[List[int]] = None)			->List[int]:



   '''simple docstring'''



   lowerCamelCase__: Optional[Any]         =[self.sep_token_id]
   lowerCamelCase__: 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]





"""simple docstring"""

def lowerCAmelCase_   (					UpperCamelCase__						:			int					, UpperCamelCase__						:			int			):






 """simple docstring"""







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


def lowerCAmelCase_   (					UpperCamelCase__						:			int					, UpperCamelCase__						:			int			):






 """simple docstring"""







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


def lowerCAmelCase_   (					UpperCamelCase__						:			int = 20			):






 """simple docstring"""







 __lowercase						=						1
 for i in range(1					, n + 1			):
  __lowercase						=						lcm(UpperCamelCase__					, UpperCamelCase__			)
 return g


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