"""simple docstring"""




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_fnet import FNetTokenizer
else:
     _a				:		Optional[Any]	   =       None

_a				:		Optional[Any]	   =       logging.get_logger(__name__)
_a				:		Union[str, Any]	   =       {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_a				:		Any	   =       {
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

_a				:		Tuple	   =       {
    'google/fnet-base': 512,
    'google/fnet-large': 512,
}

_a				:		Optional[Any]	   =       '▁'
class 						__A							(			SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      List[str]		 =		VOCAB_FILES_NAMES
     _UpperCamelCase							:      Optional[int]		 =		PRETRAINED_VOCAB_FILES_MAP
     _UpperCamelCase							:      int		 =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _UpperCamelCase							:      Dict		 =		["input_ids", "token_type_ids"]
     _UpperCamelCase							:      Union[str, Any]		 =		FNetTokenizer






     def __init__(		self    ,					a__=None    ,					a__=None    ,					a__=False    ,					a__=True    ,					a__=True    ,					a__="<unk>"    ,					a__="[SEP]"    ,					a__="<pad>"    ,					a__="[CLS]"    ,					a__="[MASK]"    ,					**a__    ,					):
       # Mask token behave like a normal word, i.e. include the space before it and
       # is included in the raw text, there should be a match in a non-normalized sentence.
       _lowerCAmelCase						:	str        =					(
           AddedToken(a__    ,					lstrip=a__    ,					rstrip=a__    ,					normalized=a__  )
           if isinstance(a__    ,					a__  )
           else mask_token
       )

       super().__init__(
           a__    ,					tokenizer_file=a__    ,					do_lower_case=a__    ,					remove_space=a__    ,					keep_accents=a__    ,					unk_token=a__    ,					sep_token=a__    ,					pad_token=a__    ,					cls_token=a__    ,					mask_token=a__    ,					**a__    ,					)

       _lowerCAmelCase						:	Optional[Any]        =					do_lower_case
       _lowerCAmelCase						:	Union[str, Any]        =					remove_space
       _lowerCAmelCase						:	List[str]        =					keep_accents
       _lowerCAmelCase						:	int        =					vocab_file
       _lowerCAmelCase						:	List[Any]        =					False if not self.vocab_file else True






     def    __A  (		self    ,					a__    ,					a__ = None  ):
       _lowerCAmelCase						:	Optional[int]        =					[self.sep_token_id]
       _lowerCAmelCase						:	int        =					[self.cls_token_id]
       if token_ids_a is None:
         return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep






     def    __A  (		self    ,					a__    ,					a__ = None  ):
       _lowerCAmelCase						:	Tuple        =					[self.sep_token_id]
       _lowerCAmelCase						:	Tuple        =					[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  ) * [0] + len(token_ids_a + sep  ) * [1]






     def    __A  (		self    ,					a__    ,					a__ = None  ):
       if not os.path.isdir(a__  ):
         logger.error(F"Vocabulary path ({save_directory}) should be a directory"  )
         return
       _lowerCAmelCase						:	Any        =					os.path.join(
           a__    ,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )

       if os.path.abspath(self.vocab_file  ) != os.path.abspath(a__  ):
         copyfile(self.vocab_file    ,					a__  )

       return (out_vocab_file,)





"""simple docstring"""




def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	int = 100     )	->				int:
  _lowerCAmelCase						:	Optional[Any]        =					n * (n + 1) * (2 * n + 1) / 6
  _lowerCAmelCase						:	Tuple        =					(n * (n + 1) / 2) ** 2
  return int(square_of_sum - sum_of_squares     )


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




