





"""simple docstring"""



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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a_					=     logging.get_logger(__name__)

a_					=     {"""vocab_file""": """sentencepiece.bpe.model"""}

a_					=     {
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
}

a_					=     {
    """moussaKam/mbarthez""": 1024,
    """moussaKam/barthez""": 1024,
    """moussaKam/barthez-orangesum-title""": 1024,
}

a_					=     """▁"""






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 _lowerCamelCase								=	VOCAB_FILES_NAMES
 _lowerCamelCase								=	PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase								=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase								=	["""input_ids""", """attention_mask"""]

 def __init__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase="<s>"   ,		__lowerCamelCase="</s>"   ,		__lowerCamelCase="</s>"   ,		__lowerCamelCase="<s>"   ,		__lowerCamelCase="<unk>"   ,		__lowerCamelCase="<pad>"   ,		__lowerCamelCase="<mask>"   ,		__lowerCamelCase = None   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		Tuple							=	AddedToken(__lowerCamelCase   ,		lstrip=__lowerCamelCase   ,		rstrip=__lowerCamelCase    ) if isinstance(__lowerCamelCase   ,		__lowerCamelCase    ) else mask_token

     __A       :		Any							=	{} if sp_model_kwargs is None else sp_model_kwargs

     super().__init__(
         bos_token=__lowerCamelCase   ,		eos_token=__lowerCamelCase   ,		unk_token=__lowerCamelCase   ,		sep_token=__lowerCamelCase   ,		cls_token=__lowerCamelCase   ,		pad_token=__lowerCamelCase   ,		mask_token=__lowerCamelCase   ,		sp_model_kwargs=self.sp_model_kwargs   ,		**__lowerCamelCase   ,		)

     __A       :		Optional[int]							=	vocab_file
     __A       :		Any							=	spm.SentencePieceProcessor(**self.sp_model_kwargs    )
     self.sp_model.Load(str(__lowerCamelCase    )    )

     __A       :		Any							=	{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

     __A       :		Tuple							=	len(self.sp_model    ) - 1
     __A       :		Any							=	{v: k for k, v in self.fairseq_tokens_to_ids.items()}

 def    UpperCamelCase__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase = None    ):



     '''simple docstring'''




     if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     __A       :		List[Any]							=	[self.cls_token_id]
     __A       :		List[Any]							=	[self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep

 def    UpperCamelCase__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase = None   ,		__lowerCamelCase = False    ):



     '''simple docstring'''




     if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=__lowerCamelCase   ,		token_ids_a=__lowerCamelCase   ,		already_has_special_tokens=__lowerCamelCase    )

     if token_ids_a is None:
         return [1] + ([0] * len(__lowerCamelCase    )) + [1]
     return [1] + ([0] * len(__lowerCamelCase    )) + [1, 1] + ([0] * len(__lowerCamelCase    )) + [1]

 def    UpperCamelCase__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase = None    ):



     '''simple docstring'''




     __A       :		Any							=	[self.sep_token_id]
     __A       :		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]

 @property
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     return len(self.sp_model    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	{self.convert_ids_to_tokens(__lowerCamelCase    ): i for i in range(self.vocab_size    )}
     vocab.update(self.added_tokens_encoder    )
     return vocab

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     return self.sp_model.encode(__lowerCamelCase   ,		out_type=__lowerCamelCase    )

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     if token in self.fairseq_tokens_to_ids:
         return self.fairseq_tokens_to_ids[token]
     __A       :		Union[str, Any]							=	self.sp_model.PieceToId(__lowerCamelCase    )

     return spm_id if spm_id else self.unk_token_id

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     if index in self.fairseq_ids_to_tokens:
         return self.fairseq_ids_to_tokens[index]
     return self.sp_model.IdToPiece(__lowerCamelCase    )

 def    UpperCamelCase__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	[]
     __A       :		Dict							=	''''''
     __A       :		Optional[Any]							=	False
     for token in tokens:
         # make sure that special tokens are not decoded using sentencepiece model
         if token in self.all_special_tokens:
             if not prev_is_special:
                 out_string += " "
             out_string += self.sp_model.decode(__lowerCamelCase    ) + token
             __A       :		List[str]							=	True
             __A       :		str							=	[]
         else:
             current_sub_tokens.append(__lowerCamelCase    )
             __A       :		Dict							=	False
     out_string += self.sp_model.decode(__lowerCamelCase    )
     return out_string.strip()

 def __getstate__(       self    ):



     '''simple docstring'''




     __A       :		int							=	self.__dict__.copy()
     __A       :		List[str]							=	None
     return state

 def __setstate__(       self   ,		__lowerCamelCase    ):



     '''simple docstring'''




     __A       :		List[Any]							=	d

     # for backward compatibility
     if not hasattr(self   ,		'''sp_model_kwargs'''    ):
         __A       :		Any							=	{}

     __A       :		Optional[int]							=	spm.SentencePieceProcessor(**self.sp_model_kwargs    )
     self.sp_model.Load(self.vocab_file    )







 def    UpperCamelCase__(       self   ,		__lowerCamelCase   ,		__lowerCamelCase = None    ):



     '''simple docstring'''




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

     if os.path.abspath(self.vocab_file    ) != os.path.abspath(__lowerCamelCase    ) and os.path.isfile(self.vocab_file    ):
         copyfile(self.vocab_file   ,		__lowerCamelCase    )
     elif not os.path.isfile(self.vocab_file    ):
         with open(__lowerCamelCase   ,		'''wb'''    ) as fi:
             __A       :		Union[str, Any]							=	self.sp_model.serialized_model_proto()
             fi.write(__lowerCamelCase    )

     return (out_vocab_file,)











"""simple docstring"""



from collections import defaultdict
from math import gcd







def 						__lowercase	(  snake_case_    :    int = 1500000		)  ->int:



    '''simple docstring'''







    __A       :		defaultdict							=	defaultdict(snake_case_		)
    __A       :		Any							=	2
    while 2 * euclid_m * (euclid_m + 1) <= limit:
        for euclid_n in range((euclid_m % 2) + 1							,snake_case_							,2		):
            if gcd(snake_case_							,snake_case_		) > 1:
                continue
            __A       :		List[Any]							=	2 * euclid_m * (euclid_m + euclid_n)
            for perimeter in range(snake_case_							,limit + 1							,snake_case_		):
                frequencies[perimeter] += 1
        euclid_m += 1
    return sum(1 for frequency in frequencies.values() if frequency == 1		)


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




