






"""simple docstring"""



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer


_lowerCAmelCase	:	int				=      logging.get_logger(__name__)

_lowerCAmelCase	:	Dict				=      {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_lowerCAmelCase	:	Union[str, Any]				=      [
    """small""",
    """small-base""",
    """medium""",
    """medium-base""",
    """intermediate""",
    """intermediate-base""",
    """large""",
    """large-base""",
    """xlarge""",
    """xlarge-base""",
]

_lowerCAmelCase	:	Optional[int]				=      {
    """vocab_file""": {
        """funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/vocab.txt""",
        """funnel-transformer/small-base""": """https://huggingface.co/funnel-transformer/small-base/resolve/main/vocab.txt""",
        """funnel-transformer/medium""": """https://huggingface.co/funnel-transformer/medium/resolve/main/vocab.txt""",
        """funnel-transformer/medium-base""": (
            """https://huggingface.co/funnel-transformer/medium-base/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/intermediate""": (
            """https://huggingface.co/funnel-transformer/intermediate/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/intermediate-base""": (
            """https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/large""": """https://huggingface.co/funnel-transformer/large/resolve/main/vocab.txt""",
        """funnel-transformer/large-base""": """https://huggingface.co/funnel-transformer/large-base/resolve/main/vocab.txt""",
        """funnel-transformer/xlarge""": """https://huggingface.co/funnel-transformer/xlarge/resolve/main/vocab.txt""",
        """funnel-transformer/xlarge-base""": (
            """https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/tokenizer.json""",
        """funnel-transformer/small-base""": (
            """https://huggingface.co/funnel-transformer/small-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/medium""": """https://huggingface.co/funnel-transformer/medium/resolve/main/tokenizer.json""",
        """funnel-transformer/medium-base""": (
            """https://huggingface.co/funnel-transformer/medium-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/intermediate""": (
            """https://huggingface.co/funnel-transformer/intermediate/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/intermediate-base""": (
            """https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/large""": """https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer.json""",
        """funnel-transformer/large-base""": (
            """https://huggingface.co/funnel-transformer/large-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/xlarge""": """https://huggingface.co/funnel-transformer/xlarge/resolve/main/tokenizer.json""",
        """funnel-transformer/xlarge-base""": (
            """https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/tokenizer.json"""
        ),
    },
}
_lowerCAmelCase	:	Any				=      {F"""funnel-transformer/{name}""": 512 for name in _model_names}
_lowerCAmelCase	:	Tuple				=      {F"""funnel-transformer/{name}""": {"""do_lower_case""": True} for name in _model_names}




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    =VOCAB_FILES_NAMES
   SCREAMING_SNAKE_CASE_    =PRETRAINED_VOCAB_FILES_MAP
   SCREAMING_SNAKE_CASE_    =PRETRAINED_INIT_CONFIGURATION
   SCREAMING_SNAKE_CASE_    =FunnelTokenizer
   SCREAMING_SNAKE_CASE_    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   SCREAMING_SNAKE_CASE_    =2
   def __init__(		self      :	str							,			snake_case__      :	Union[str, Any]=None							,			snake_case__      :	List[Any]=None							,			snake_case__      :	Union[str, Any]=True							,			snake_case__      :	Dict="<unk>"							,			snake_case__      :	Optional[int]="<sep>"							,			snake_case__      :	Union[str, Any]="<pad>"							,			snake_case__      :	Optional[int]="<cls>"							,			snake_case__      :	Optional[Any]="<mask>"							,			snake_case__      :	Optional[int]="<s>"							,			snake_case__      :	Dict="</s>"							,			snake_case__      :	Tuple=True							,			snake_case__      :	Optional[Any]=True							,			snake_case__      :	Union[str, Any]=None							,			snake_case__      :	List[Any]="##"							,			**snake_case__      :	int							,			):


        '''simple docstring'''
        super().__init__(
            snake_case__							,			tokenizer_file=snake_case__							,			do_lower_case=snake_case__							,			unk_token=snake_case__							,			sep_token=snake_case__							,			pad_token=snake_case__							,			cls_token=snake_case__							,			mask_token=snake_case__							,			bos_token=snake_case__							,			eos_token=snake_case__							,			clean_text=snake_case__							,			tokenize_chinese_chars=snake_case__							,			strip_accents=snake_case__							,			wordpieces_prefix=snake_case__							,			**snake_case__							,			)

        UpperCAmelCase__						:    Tuple							=							json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
        if (
            normalizer_state.get("lowercase"							,			snake_case__							) != do_lower_case
            or normalizer_state.get("strip_accents"							,			snake_case__							) != strip_accents
            or normalizer_state.get("handle_chinese_chars"							,			snake_case__							) != tokenize_chinese_chars
        ):
             UpperCAmelCase__						:    Dict							=							getattr(snake_case__							,			normalizer_state.pop("type"							)							)
             UpperCAmelCase__						:    Any							=							do_lower_case
             UpperCAmelCase__						:    Optional[Any]							=							strip_accents
             UpperCAmelCase__						:    Any							=							tokenize_chinese_chars
             UpperCAmelCase__						:    Tuple							=							normalizer_class(**snake_case__							)

        UpperCAmelCase__						:    Union[str, Any]							=							do_lower_case
   def       __a							(		self      :	Union[str, Any]							,			snake_case__      :	Union[str, Any]							,			snake_case__      :	Dict=None							):


        '''simple docstring'''
        UpperCAmelCase__						:    Dict							=							[self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
             output += token_ids_a + [self.sep_token_id]

        return output
   def       __a							(		self      :	Tuple							,			snake_case__      :	List[int]							,			snake_case__      :	Optional[List[int]] = None							):


        '''simple docstring'''
        UpperCAmelCase__						:    str							=							[self.sep_token_id]
        UpperCAmelCase__						:    Union[str, Any]							=							[self.cls_token_id]
        if token_ids_a is None:
             return len(cls							) * [self.cls_token_type_id] + len(token_ids_a + sep							) * [0]
        return len(cls							) * [self.cls_token_type_id] + len(token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]




   def       __a							(		self      :	List[Any]							,			snake_case__      :	str							,			snake_case__      :	Optional[str] = None							):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							self._tokenizer.model.save(snake_case__							,			name=snake_case__							)
        return tuple(snake_case__							)










"""simple docstring"""



import os


def 	SCREAMING_SNAKE_CASE__       (  )->		Optional[Any]:






     '''simple docstring'''



     with open(os.path.dirname(snake_case				) + "/p022_names.txt"				) as file:
          UpperCAmelCase__						:    Tuple							=							str(file.readlines()[0]				)
          UpperCAmelCase__						:    str							=							names.replace("\""			,					""				).split(","				)

     names.sort()

     UpperCAmelCase__						:    Optional[int]							=							0
     UpperCAmelCase__						:    List[str]							=							0

     for i, name in enumerate(snake_case				):
          for letter in name:
               name_score += ord(snake_case				) - 64

          total_score += (i + 1) * name_score
          UpperCAmelCase__						:    Optional[int]							=							0
     return total_score


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


