
"""simple docstring"""




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

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


if is_sentencepiece_available():
    from .tokenization_xglm import XGLMTokenizer
else:
    a		:					Dict    	=					None


a		:					Optional[Any]    	=					logging.get_logger(__name__)

a		:					str    	=					{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

a		:					List[str]    	=					{
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json',
    },
}

a		:					Optional[int]    	=					{
    'facebook/xglm-564M': 20_48,
}







class 						lowercase(_lowercase					):
     __snake_case:  str  				=    VOCAB_FILES_NAMES
     __snake_case:  List[str]  				=    PRETRAINED_VOCAB_FILES_MAP
     __snake_case:  List[Any]  				=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __snake_case:  Tuple  				=    ['input_ids', 'attention_mask']
     __snake_case:  Tuple  				=    XGLMTokenizer



     def __init__(       self    ,							__SCREAMING_SNAKE_CASE=None    ,							__SCREAMING_SNAKE_CASE=None    ,							__SCREAMING_SNAKE_CASE="<s>"    ,							__SCREAMING_SNAKE_CASE="</s>"    ,							__SCREAMING_SNAKE_CASE="</s>"    ,							__SCREAMING_SNAKE_CASE="<s>"    ,							__SCREAMING_SNAKE_CASE="<unk>"    ,							__SCREAMING_SNAKE_CASE="<pad>"    ,							**__SCREAMING_SNAKE_CASE    ,							)		->    str:







         """simple docstring"""



         a__    = 7
         a__    = [f'<madeupword{i}>' for i in range(self.num_madeup_words      )]

         a__    = kwargs.get('additional_special_tokens'    ,							[]      )
         kwargs["additional_special_tokens"] += [
             word for word in madeup_words if word not in kwargs["additional_special_tokens"]
         ]

         super().__init__(
             __SCREAMING_SNAKE_CASE    ,							tokenizer_file=__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    ,							**__SCREAMING_SNAKE_CASE    ,							)

         a__    = vocab_file
         a__    = False if not self.vocab_file else True



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None      )		->    List[int]:







         """simple docstring"""



         if token_ids_a is None:
             return [self.sep_token_id] + token_ids_a
         a__    = [self.sep_token_id]
         return sep + token_ids_a + sep + sep + token_ids_a



     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None      )		->    List[int]:







         """simple docstring"""



         a__    = [self.sep_token_id]

         if token_ids_a is None:
             return len(sep + token_ids_a      ) * [0]
         return len(sep + token_ids_a + sep + sep + token_ids_a      ) * [0]




     def  lowercase__     (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None      )		->    Tuple[str]:







         """simple docstring"""



         if not self.can_save_slow_tokenizer:
             raise ValueError(
                 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                 'tokenizer.'      )

         if not os.path.isdir(__SCREAMING_SNAKE_CASE      ):
             logger.error(f'Vocabulary path ({save_directory}) should be a directory.'      )
             return
         a__    = os.path.join(
             __SCREAMING_SNAKE_CASE    ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

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

         return (out_vocab_file,)




"""simple docstring"""




from itertools import combinations, product



def 						__magic_name__		(				UpperCamelCase    :		int       ,		UpperCamelCase    :		int       ,		UpperCamelCase    :		int       ,		UpperCamelCase    :		int    )    ->	bool:
    if xa == ya == 0 or xa == ya == 0:
        return False
    a__    = xa * xa + ya * ya
    a__    = xa * xa + ya * ya
    a__    = (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
    return (
        a_square + b_square == c_square
        or a_square + c_square == b_square
        or b_square + c_square == a_square
    )



def 						__magic_name__		(				UpperCamelCase    :		int = 50    )    ->	int:
    return sum(
        1
        for pta, pta in combinations(product(range(limit + 1    )       ,		repeat=2    )       ,		2    )
        if is_right(*UpperCamelCase       ,		*UpperCamelCase    )    )


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


