





from __future__ import annotations




def    A_(			A				,      A = None				,      A = None   ):
	if start is None:
		UpperCAmelCase_								=     0

	if end is None:
		UpperCAmelCase_								=     len(__lowerCAmelCase   ) - 1

	if start >= end:
		return

	UpperCAmelCase_								=     (start + end) // 2

	slowsort(__lowerCAmelCase				,      __lowerCAmelCase				,      __lowerCAmelCase   )
	slowsort(__lowerCAmelCase				,      mid + 1				,      __lowerCAmelCase   )

	if sequence[end] < sequence[mid]:
		UpperCAmelCase_								=     sequence[mid], sequence[end]

	slowsort(__lowerCAmelCase				,      __lowerCAmelCase				,      end - 1   )


if __name__ == "__main__":
				from doctest import testmod

				testmod()









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


UpperCamelCase__   : List[str]					  = logging.get_logger(__name__)

UpperCamelCase__   : int					  = """▁"""

UpperCamelCase__   : Dict					  = {"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

UpperCamelCase__   : Dict					  = {
    """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""",
    },
}

UpperCamelCase__   : Optional[int]					  = {"""vinai/bartpho-syllable""": 10_24}







class   _UpperCamelCase  (       A_  ):







					'''simple docstring'''

					lowerCamelCase     :     str			    =       VOCAB_FILES_NAMES
					lowerCamelCase     :     Optional[int]			    =       PRETRAINED_VOCAB_FILES_MAP
					lowerCamelCase     :     List[str]			    =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCamelCase     :     Optional[Any]			    =       ['input_ids', 'attention_mask']





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






						'''simple docstring'''







						UpperCAmelCase_								=     AddedToken(__lowercase ,					lstrip=__lowercase ,					rstrip=__lowercase		) if isinstance(__lowercase ,					__lowercase		) else mask_token

						UpperCAmelCase_								=     {} if sp_model_kwargs is None else sp_model_kwargs

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

						UpperCAmelCase_								=     vocab_file
						UpperCAmelCase_								=     monolingual_vocab_file
						UpperCAmelCase_								=     spm.SentencePieceProcessor(**self.sp_model_kwargs		)
						self.sp_model.Load(str(__lowercase		)		)

						# Load the reduced vocab

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

						UpperCAmelCase_								=     {v: k for k, v in self.fairseq_tokens_to_ids.items()}





					def __getstate__(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.__dict__.copy()
						UpperCAmelCase_								=     None
						UpperCAmelCase_								=     self.sp_model.serialized_model_proto()
						return state





					def __setstate__(						self    :  List[str] ,					__lowercase    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     d

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

						UpperCAmelCase_								=     spm.SentencePieceProcessor(**self.sp_model_kwargs		)
						self.sp_model.LoadFromSerializedProto(self.sp_model_proto		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Union[str, Any] ,					__lowercase    :  List[int] ,					__lowercase    :  Optional[List[int]] = None		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any] ,					__lowercase    :  List[int] ,					__lowercase    :  Optional[List[int]] = None ,					__lowercase    :  bool = False		):






						'''simple docstring'''







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

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





					def        SCREAMING_SNAKE_CASE							(						self    :  Any ,					__lowercase    :  List[int] ,					__lowercase    :  Optional[List[int]] = None		):






						'''simple docstring'''







						UpperCAmelCase_								=     [self.sep_token_id]
						UpperCAmelCase_								=     [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        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						return len(self.fairseq_ids_to_tokens		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     {self.convert_ids_to_tokens(__lowercase		): i for i in range(self.vocab_size		)}
						vocab.update(self.added_tokens_encoder		)
						return vocab





					def        SCREAMING_SNAKE_CASE							(						self    :  str ,					__lowercase    :  str		):






						'''simple docstring'''







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





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple ,					__lowercase    :  Tuple		):






						'''simple docstring'''







						if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
						else:
							return self.unk_token_id





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict ,					__lowercase    :  Optional[Any]		):






						'''simple docstring'''







						return self.fairseq_ids_to_tokens[index]





					def        SCREAMING_SNAKE_CASE							(						self    :  Any ,					__lowercase    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     """""".join(__lowercase		).replace(__lowercase ,					""" """		).strip()
						return out_string





					def        SCREAMING_SNAKE_CASE							(						self    :  str ,					__lowercase    :  str ,					__lowercase    :  Optional[str] = None		):






						'''simple docstring'''







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

						if os.path.abspath(self.vocab_file		) != os.path.abspath(__lowercase		) and os.path.isfile(self.vocab_file		):
							copyfile(self.vocab_file ,					__lowercase		)
						elif not os.path.isfile(self.vocab_file		):
							with open(__lowercase ,					"""wb"""		) as fi:
								UpperCAmelCase_								=     self.sp_model.serialized_model_proto()
								fi.write(__lowercase		)

						if os.path.abspath(self.monolingual_vocab_file		) != os.path.abspath(
						    __lowercase		) and os.path.isfile(self.monolingual_vocab_file		):
							copyfile(self.monolingual_vocab_file ,					__lowercase		)
						elif not os.path.isfile(self.monolingual_vocab_file		):
							with open(__lowercase ,					"""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(__lowercase		)} \n"""		)

						return out_vocab_file, out_monolingual_vocab_file


