

'''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


__snake_case			:     Union[str, Any]										=      logging.get_logger(__name__)

__snake_case			:     str										=      '▁'

__snake_case			:     str										=      {'vocab_file': 'sentencepiece.bpe.model'}

__snake_case			:     Tuple										=      {
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

__snake_case			:     int										=      {
    'xlm-roberta-base': 512,
    'xlm-roberta-large': 512,
    'xlm-roberta-large-finetuned-conll02-dutch': 512,
    'xlm-roberta-large-finetuned-conll02-spanish': 512,
    'xlm-roberta-large-finetuned-conll03-english': 512,
    'xlm-roberta-large-finetuned-conll03-german': 512,
}



class lowerCamelCase			(  __lowerCAmelCase						):



			'''simple docstring'''






			__snake_case        =	VOCAB_FILES_NAMES
			__snake_case        =	PRETRAINED_VOCAB_FILES_MAP
			__snake_case        =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__snake_case        =	['''input_ids''', '''attention_mask''']


			def __init__(				self	:						str		,      lowerCAmelCase_	:						str		,      lowerCAmelCase_	:						str="<s>"		,      lowerCAmelCase_	:						str="</s>"		,      lowerCAmelCase_	:						str="</s>"		,      lowerCAmelCase_	:						Tuple="<s>"		,      lowerCAmelCase_	:						Optional[int]="<unk>"		,      lowerCAmelCase_	:						Optional[int]="<pad>"		,      lowerCAmelCase_	:						Dict="<mask>"		,      lowerCAmelCase_	:						List[Any] = None		,      **lowerCAmelCase_	:						int		,      )      ->		None:





									'''simple docstring'''
									# Mask token behave like a normal word, i.e. include the space before it
									A__					:       List[Any]     =AddedToken(lowerCAmelCase_		,      lstrip=lowerCAmelCase_		,      rstrip=lowerCAmelCase_			) if isinstance(lowerCAmelCase_		,      lowerCAmelCase_			) else mask_token

									A__					:       int     ={} 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]     =spm.SentencePieceProcessor(**self.sp_model_kwargs			)
									self.sp_model.Load(str(lowerCAmelCase_			)			)
									A__					:       Optional[int]     =vocab_file

									# Original fairseq vocab and spm vocab must be "aligned":
									# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
									# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
									# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
									# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

									# Mimic fairseq token-to-id alignment for the first 4 token
									A__					:       List[str]     ={"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

									# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
									A__					:       Tuple     =1

									A__					:       int     =len(self.sp_model			) + self.fairseq_offset
									A__					:       int     ={v: k for k, v in self.fairseq_tokens_to_ids.items()}


			def __getstate__(				self	:						str			)      ->		int:





									'''simple docstring'''
									A__					:       List[str]     =self.__dict__.copy()
									A__					:       Optional[Any]     =None
									A__					:       Union[str, Any]     =self.sp_model.serialized_model_proto()
									return state


			def __setstate__(				self	:						Tuple		,      lowerCAmelCase_	:						int			)      ->		Dict:





									'''simple docstring'''
									A__					:       int     =d

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

									A__					:       List[str]     =spm.SentencePieceProcessor(**self.sp_model_kwargs			)
									self.sp_model.LoadFromSerializedProto(self.sp_model_proto			)


			def lowercase__						(				self	:						str		,      lowerCAmelCase_	:						str		,      lowerCAmelCase_	:						Any = None			)      ->		List[int]:





									'''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 lowercase__						(				self	:						Any		,      lowerCAmelCase_	:						Optional[Any]		,      lowerCAmelCase_	:						List[Any] = None		,      lowerCAmelCase_	:						List[str] = False			)      ->		List[int]:





									'''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 lowercase__						(				self	:						str		,      lowerCAmelCase_	:						Any		,      lowerCAmelCase_	:						Any = None			)      ->		List[int]:





									'''simple docstring'''
									A__					:       Dict     =[self.sep_token_id]
									A__					:       str     =[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 lowercase__						(				self	:						str			)      ->		List[Any]:





									'''simple docstring'''
									return len(self.sp_model			) + self.fairseq_offset + 1  # Add the <mask> token


			def lowercase__						(				self	:						str			)      ->		Optional[int]:





									'''simple docstring'''
									A__					:       Dict     ={self.convert_ids_to_tokens(lowerCAmelCase_			): i for i in range(self.vocab_size			)}
									vocab.update(self.added_tokens_encoder			)
									return vocab


			def lowercase__						(				self	:						List[Any]		,      lowerCAmelCase_	:						Dict			)      ->		List[str]:





									'''simple docstring'''
									return self.sp_model.encode(lowerCAmelCase_		,      out_type=lowerCAmelCase_			)


			def lowercase__						(				self	:						Dict		,      lowerCAmelCase_	:						List[str]			)      ->		List[Any]:





									'''simple docstring'''
									if token in self.fairseq_tokens_to_ids:
															return self.fairseq_tokens_to_ids[token]
									A__					:       Optional[Any]     =self.sp_model.PieceToId(lowerCAmelCase_			)

									# Need to return unknown token if the SP model returned 0
									return spm_id + self.fairseq_offset if spm_id else self.unk_token_id


			def lowercase__						(				self	:						Dict		,      lowerCAmelCase_	:						Dict			)      ->		Any:





									'''simple docstring'''
									if index in self.fairseq_ids_to_tokens:
															return self.fairseq_ids_to_tokens[index]
									return self.sp_model.IdToPiece(index - self.fairseq_offset			)


			def lowercase__						(				self	:						Dict		,      lowerCAmelCase_	:						Dict			)      ->		Union[str, Any]:





									'''simple docstring'''
									A__					:       int     ="""""".join(lowerCAmelCase_			).replace(lowerCAmelCase_		,      """ """			).strip()
									return out_string



			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						Dict		,      lowerCAmelCase_	:						int = None			)      ->		Tuple[str]:





									'''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__					:       str     =self.sp_model.serialized_model_proto()
																					fi.write(lowerCAmelCase_			)

									return (out_vocab_file,)


'''simple docstring'''



from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def 						__lowerCamelCase	(       __snake_case					:		int	)	->							int:






						"""simple docstring"""





						A__					:       List[Any]     =prime_factors(__snake_case	)
						if is_square_free(__snake_case	):
												return -1 if len(__snake_case	) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

