



"""simple docstring"""







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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A		=						logging.get_logger(__name__)

A		=						{'vocab_file': 'sentencepiece.model'}

A		=						{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

A		=						{
    'google/rembert': 2_5_6,
}

class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     VOCAB_FILES_NAMES
			__magic_name__     					=     PRETRAINED_VOCAB_FILES_MAP
			__magic_name__     					=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



			def __init__(			self							:				Union[str, Any]   ,	_lowercase							:				Union[str, Any]   ,	_lowercase							:				Optional[int]=False   ,	_lowercase							:				Union[str, Any]=True   ,	_lowercase							:				Union[str, Any]=True   ,	_lowercase							:				Optional[int]="[CLS]"   ,	_lowercase							:				Tuple="[SEP]"   ,	_lowercase							:				Optional[Any]="[UNK]"   ,	_lowercase							:				Dict="[SEP]"   ,	_lowercase							:				Optional[Any]="[PAD]"   ,	_lowercase							:				int="[CLS]"   ,	_lowercase							:				Any="[MASK]"   ,	**_lowercase							:				Tuple   ,	)							->					List[str]:
									super().__init__(
									    do_lower_case=_lowercase   ,	remove_space=_lowercase   ,	keep_accents=_lowercase   ,	bos_token=_lowercase   ,	eos_token=_lowercase   ,	unk_token=_lowercase   ,	sep_token=_lowercase   ,	pad_token=_lowercase   ,	cls_token=_lowercase   ,	mask_token=_lowercase   ,	**_lowercase   ,	)

									snake_case   :			Tuple						    = do_lower_case
									snake_case   :			Optional[Any]						    = remove_space
									snake_case   :			int						    = keep_accents
									snake_case   :			Optional[int]						    = vocab_file

									snake_case   :			str						    = spm.SentencePieceProcessor()
									self.sp_model.Load(_lowercase		)



			@property
			def 				__lowercase					(			self							:				int		)							->					Dict:
									return len(self.sp_model		)



			def 				__lowercase					(			self							:				List[str]		)							->					Dict:
									snake_case   :			int						    = {self.convert_ids_to_tokens(_lowercase		): i for i in range(self.vocab_size		)}
									vocab.update(self.added_tokens_encoder		)
									return vocab



			def __getstate__(			self							:				Tuple		)							->					Any:
									snake_case   :			Optional[Any]						    = self.__dict__.copy()
									snake_case   :			List[str]						    = None
									return state



			def __setstate__(			self							:				Any   ,	_lowercase							:				Optional[Any]		)							->					Optional[Any]:
									snake_case   :			Tuple						    = d
									snake_case   :			Optional[Any]						    = spm.SentencePieceProcessor()
									self.sp_model.Load(self.vocab_file		)



			def 				__lowercase					(			self							:				Any   ,	_lowercase							:				Any   ,	_lowercase							:				Any=False		)							->					Dict:
									snake_case   :			Tuple						    = self.sp_model.EncodeAsPieces(_lowercase		)
									return pieces



			def 				__lowercase					(			self							:				Optional[int]   ,	_lowercase							:				List[Any]		)							->					Dict:
									return self.sp_model.PieceToId(_lowercase		)



			def 				__lowercase					(			self							:				List[str]   ,	_lowercase							:				List[str]		)							->					List[Any]:
									return self.sp_model.IdToPiece(_lowercase		)



			def 				__lowercase					(			self							:				Optional[Any]   ,	_lowercase							:				Union[str, Any]		)							->					List[str]:
									snake_case   :			Optional[int]						    = self.sp_model.decode_pieces(_lowercase		)
									return out_string



			def 				__lowercase					(			self							:				Dict   ,	_lowercase							:				List[int]   ,	_lowercase							:				Optional[List[int]] = None		)							->					List[int]:
									snake_case   :			int						    = [self.sep_token_id]
									snake_case   :			Optional[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 				__lowercase					(			self							:				Tuple   ,	_lowercase							:				List[int]   ,	_lowercase							:				Optional[List[int]] = None   ,	_lowercase							:				bool = False		)							->					List[int]:

									if already_has_special_tokens:
															if token_ids_a is not None:
																					raise ValueError(
																					    "You should not supply a second sequence if the provided sequence of "
																					    "ids is already formatted with special tokens for the model."		)
															return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

									if token_ids_a is not None:
															return [1] + ([0] * len(_lowercase		)) + [1] + ([0] * len(_lowercase		)) + [1]
									return [1] + ([0] * len(_lowercase		)) + [1]



			def 				__lowercase					(			self							:				Tuple   ,	_lowercase							:				List[int]   ,	_lowercase							:				Optional[List[int]] = None		)							->					List[int]:
									snake_case   :			Tuple						    = [self.sep_token_id]
									snake_case   :			List[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		) * [0] + len(token_ids_a + sep		) * [1]



			def 				__lowercase					(			self							:				Optional[int]   ,	_lowercase							:				str   ,	_lowercase							:				Optional[str] = None		)							->					Tuple[str]:
									if not os.path.isdir(_lowercase		):
															logger.error("Vocabulary path ({}) should be a directory".format(_lowercase		)		)
															return
									snake_case   :			Union[str, Any]						    = os.path.join(
									    _lowercase   ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

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

									return (out_vocab_file,)








"""simple docstring"""







def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int     ,		lowerCamelCase_:							int ):
						"""simple docstring"""






						return int((input_a, input_a).count(0 ) != 0 )

def  __SCREAMING_SNAKE_CASE		(			):
						"""simple docstring"""






						assert nand_gate(0     ,		0 ) == 1
						assert nand_gate(0     ,		1 ) == 1
						assert nand_gate(1     ,		0 ) == 1
						assert nand_gate(1     ,		1 ) == 0


if __name__ == "__main__":
			print(nand_gate(0, 0))
			print(nand_gate(0, 1))
			print(nand_gate(1, 0))
			print(nand_gate(1, 1))



