


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


lowerCamelCase						=		logging.get_logger(__name__)

lowerCamelCase						=		'''▁'''

lowerCamelCase						=		{'''vocab_file''': '''sentencepiece.bpe.model''', '''monolingual_vocab_file''': '''dict.txt'''}

lowerCamelCase						=		{
    '''vocab_file''': {
        '''vinai/bartpho-syllable''': '''https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model''',
    },
    '''monolingual_vocab_file''': {
        '''vinai/bartpho-syllable''': '''https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt''',
    },
}

lowerCamelCase						=		{'''vinai/bartpho-syllable''': 1024}





class  _a							(    _lowercase):
	_a  :  Tuple				   =							VOCAB_FILES_NAMES
	_a  :  int				   =							PRETRAINED_VOCAB_FILES_MAP
	_a  :  str				   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_a  :  Optional[int]				   =							['''input_ids''', '''attention_mask''']




	def __init__( self						:		Tuple		, _SCREAMING_SNAKE_CASE						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		Dict		, _SCREAMING_SNAKE_CASE						:		Tuple="<s>"		, _SCREAMING_SNAKE_CASE						:		Union[str, Any]="</s>"		, _SCREAMING_SNAKE_CASE						:		List[str]="</s>"		, _SCREAMING_SNAKE_CASE						:		Tuple="<s>"		, _SCREAMING_SNAKE_CASE						:		Optional[Any]="<unk>"		, _SCREAMING_SNAKE_CASE						:		Any="<pad>"		, _SCREAMING_SNAKE_CASE						:		str="<mask>"		, _SCREAMING_SNAKE_CASE						:		Optional[Dict[str, Any]] = None		, **_SCREAMING_SNAKE_CASE						:		Optional[Any]		, )->	None:
			# Mask token behave like a normal word, i.e. include the space before it
			lowerCAmelCase__       :      int   					= AddedToken(_SCREAMING_SNAKE_CASE		, lstrip=_SCREAMING_SNAKE_CASE		, rstrip=_SCREAMING_SNAKE_CASE		) if isinstance(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		) else mask_token

			lowerCAmelCase__       :      Dict   					= {} if sp_model_kwargs is None else sp_model_kwargs

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

			lowerCAmelCase__       :      Optional[int]   					= vocab_file
			lowerCAmelCase__       :      Optional[Any]   					= monolingual_vocab_file
			lowerCAmelCase__       :      List[Any]   					= spm.SentencePieceProcessor(**self.sp_model_kwargs		)
			self.sp_model.Load(str(_SCREAMING_SNAKE_CASE		)		)

			# Load the reduced vocab

			# Keep order of special tokens for backward compatibility
			lowerCAmelCase__       :      List[Any]   					= {}
			lowerCAmelCase__       :      List[str]   					= 0
			for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
					if str(_SCREAMING_SNAKE_CASE		) not in self.fairseq_tokens_to_ids:
							lowerCAmelCase__       :      Tuple   					= cnt
							cnt += 1
			with open(_SCREAMING_SNAKE_CASE		, '''r'''		, encoding='''utf-8'''		) as f:
					for line in f.readlines():
							lowerCAmelCase__       :      List[Any]   					= line.strip().split()[0]
							lowerCAmelCase__       :      Optional[int]   					= len(self.fairseq_tokens_to_ids		)
			if str(_SCREAMING_SNAKE_CASE		) not in self.fairseq_tokens_to_ids:
					lowerCAmelCase__       :      Optional[int]   					= len(self.fairseq_tokens_to_ids		)

			lowerCAmelCase__       :      List[str]   					= {v: k for k, v in self.fairseq_tokens_to_ids.items()}




	def __getstate__( self						:		Tuple		)->	List[str]:
			lowerCAmelCase__       :      List[Any]   					= self.__dict__.copy()
			lowerCAmelCase__       :      Union[str, Any]   					= None
			lowerCAmelCase__       :      int   					= self.sp_model.serialized_model_proto()
			return state




	def __setstate__( self						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		Optional[Any]		)->	Dict:
			lowerCAmelCase__       :      Dict   					= d

			# for backward compatibility
			if not hasattr(self		, '''sp_model_kwargs'''		):
					lowerCAmelCase__       :      List[str]   					= {}

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




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		)->	List[int]:

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




	def 							UpperCAmelCase__( self						:		Tuple		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		, _SCREAMING_SNAKE_CASE						:		bool = False		)->	List[int]:

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

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




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		List[int]		, _SCREAMING_SNAKE_CASE						:		Optional[List[int]] = None		)->	List[int]:
			lowerCAmelCase__       :      Tuple   					= [self.sep_token_id]
			lowerCAmelCase__       :      Union[str, 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						:		List[str]		)->	Optional[Any]:
			return len(self.fairseq_ids_to_tokens		)




	def 							UpperCAmelCase__( self						:		List[str]		)->	str:
			lowerCAmelCase__       :      str   					= {self.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		): i for i in range(self.vocab_size		)}
			vocab.update(self.added_tokens_encoder		)
			return vocab




	def 							UpperCAmelCase__( self						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		str		)->	List[str]:
			return self.sp_model.encode(_SCREAMING_SNAKE_CASE		, out_type=_SCREAMING_SNAKE_CASE		)




	def 							UpperCAmelCase__( self						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Optional[Any]:
			if token in self.fairseq_tokens_to_ids:
					return self.fairseq_tokens_to_ids[token]
			else:
					return self.unk_token_id




	def 							UpperCAmelCase__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Any:
			return self.fairseq_ids_to_tokens[index]




	def 							UpperCAmelCase__( self						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		Optional[Any]		)->	Union[str, Any]:
			lowerCAmelCase__       :      Dict   					= ''''''.join(_SCREAMING_SNAKE_CASE		).replace(_SCREAMING_SNAKE_CASE		, ''' '''		).strip()
			return out_string




	def 							UpperCAmelCase__( self						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		str		, _SCREAMING_SNAKE_CASE						:		Optional[str] = None		)->	Tuple[str]:
			if not os.path.isdir(_SCREAMING_SNAKE_CASE		):
					logger.error(F'Vocabulary path ({save_directory}) should be a directory'		)
					return
			lowerCAmelCase__       :      str   					= os.path.join(
			    _SCREAMING_SNAKE_CASE		, (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)
			lowerCAmelCase__       :      Dict   					= os.path.join(
			    _SCREAMING_SNAKE_CASE		, (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''monolingual_vocab_file''']		, )

			if os.path.abspath(self.vocab_file		) != os.path.abspath(_SCREAMING_SNAKE_CASE		) and os.path.isfile(self.vocab_file		):
					copyfile(self.vocab_file		, _SCREAMING_SNAKE_CASE		)
			elif not os.path.isfile(self.vocab_file		):
					with open(_SCREAMING_SNAKE_CASE		, '''wb'''		) as fi:
							lowerCAmelCase__       :      Dict   					= self.sp_model.serialized_model_proto()
							fi.write(_SCREAMING_SNAKE_CASE		)

			if os.path.abspath(self.monolingual_vocab_file		) != os.path.abspath(
			    _SCREAMING_SNAKE_CASE		) and os.path.isfile(self.monolingual_vocab_file		):
					copyfile(self.monolingual_vocab_file		, _SCREAMING_SNAKE_CASE		)
			elif not os.path.isfile(self.monolingual_vocab_file		):
					with open(_SCREAMING_SNAKE_CASE		, '''w'''		, encoding='''utf-8'''		) as fp:
							for token in self.fairseq_tokens_to_ids:
									if token not in self.all_special_tokens:
											fp.write(F'{str(_SCREAMING_SNAKE_CASE		)} \n'		)

			return out_vocab_file, out_monolingual_vocab_file








def 					lowerCamelCase_   (	_a	):




		"""simple docstring"""






		if number < 0:
				raise ValueError('''number must not be negative'''	)
		return number & (number - 1) == 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()




