





"""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


__UpperCAmelCase						=			logging.get_logger(__name__)


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

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

__UpperCAmelCase						=			{
    '''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  ):
				__lowerCamelCase				:	str				     =				VOCAB_FILES_NAMES
				__lowerCamelCase				:	Optional[int]				     =				PRETRAINED_VOCAB_FILES_MAP
				__lowerCamelCase				:	List[str]				     =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__lowerCamelCase				:	Optional[int]				     =				["input_ids", "attention_mask"]
				__lowerCamelCase				:	Any				     =				BartTokenizer
				def __init__(		self    :			Any	, a_    :			Optional[Any]=None	, a_    :			List[Any]=None	, a_    :			str=None	, a_    :			List[str]="replace"	, a_    :			Optional[int]="<s>"	, a_    :			Dict="</s>"	, a_    :			List[str]="</s>"	, a_    :			Union[str, Any]="<s>"	, a_    :			Tuple="<unk>"	, a_    :			Dict="<pad>"	, a_    :			List[Any]="<mask>"	, a_    :			str=False	, a_    :			List[Any]=True	, **a_    :			List[str]	, )	->	int:



							'''simple docstring'''



							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_	, )

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

							a__  :	List[str]		 =			add_prefix_space

							# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
							a__  :	Optional[Any]		 =			"post_processor"
							a__  :	Optional[int]		 =			getattr(self.backend_tokenizer	, a_	, a_    )
							if tokenizer_component_instance:
										a__  :	int		 =			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__  :	Optional[int]		 =			tuple(state["sep"]    )
										if "cls" in state:
													a__  :	Union[str, Any]		 =			tuple(state["cls"]    )

										a__  :	str		 =			False

										if state.get("add_prefix_space"	, a_    ) != add_prefix_space:
													a__  :	Dict		 =			add_prefix_space
													a__  :	List[Any]		 =			True

										if state.get("trim_offsets"	, a_    ) != trim_offsets:
													a__  :	Optional[Any]		 =			trim_offsets
													a__  :	Optional[int]		 =			True

										if changes_to_apply:
													a__  :	Any		 =			getattr(a_	, state.pop("type"    )    )
													a__  :	List[str]		 =			component_class(**a_    )
													setattr(self.backend_tokenizer	, a_	, a_    )
				@property
				def       UpperCAmelCase      (		self    :			Dict    )	->	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       UpperCAmelCase      (		self    :			Tuple	, a_    :			List[str]    )	->	Union[str, Any]:



							'''simple docstring'''



							a__  :	Dict		 =			AddedToken(a_	, lstrip=a_	, rstrip=a_    ) if isinstance(a_	, a_    ) else value
							a__  :	List[str]		 =			value
				def       UpperCAmelCase      (		self    :			int	, *a_    :			Tuple	, **a_    :			List[str]    )	->	BatchEncoding:



							'''simple docstring'''



							a__  :	int		 =			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       UpperCAmelCase      (		self    :			Union[str, Any]	, *a_    :			Dict	, **a_    :			List[Any]    )	->	BatchEncoding:



							'''simple docstring'''



							a__  :	str		 =			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       UpperCAmelCase      (		self    :			Tuple	, a_    :			str	, a_    :			Optional[str] = None    )	->	Tuple[str]:



							'''simple docstring'''



							a__  :	Optional[int]		 =			self._tokenizer.model.save(a_	, name=a_    )
							return tuple(a_    )
				def       UpperCAmelCase      (		self    :			int	, a_    :			Union[str, Any]	, a_    :			Any=None    )	->	Any:



							'''simple docstring'''



							a__  :	Optional[Any]		 =			[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    :			Dict	, a_    :			List[int]	, a_    :			Optional[List[int]] = None    )	->	List[int]:



							'''simple docstring'''



							a__  :	List[Any]		 =			[self.sep_token_id]
							a__  :	Optional[Any]		 =			[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"""






import os






def      lowercase__ (					)    ->			Optional[Any]:



			'''simple docstring'''
			with open(os.path.dirname(lowerCAmelCase__			) + "/p022_names.txt"			) as file:
						a__  :	Optional[int]		 =			str(file.readlines()[0]			)
						a__  :	Optional[int]		 =			names.replace("\""							,			""			).split(","			)

			names.sort()

			a__  :	int		 =			0
			a__  :	Dict		 =			0

			for i, name in enumerate(lowerCAmelCase__			):
						for letter in name:
									name_score += ord(lowerCAmelCase__			) - 6_4

						total_score += (i + 1) * name_score
						a__  :	Tuple		 =			0
			return total_score


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