



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

import sentencepiece as spm

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


UpperCamelCase__ =						logging.get_logger(__name__)

UpperCamelCase__ =						{"vocab_file": "spiece.model"}

UpperCamelCase__ =						{
    "vocab_file": {
        "bert_for_seq_generation": (
            "https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"
        ),
    }
}

UpperCamelCase__ =						{"bert_for_seq_generation": 5_12}
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  Tuple      =			VOCAB_FILES_NAMES
			lowercase__      :  List[Any]      =			PRETRAINED_VOCAB_FILES_MAP
			lowercase__      :  int      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowercase__      :  List[int]      =			[]
			lowercase__      :  Dict      =			["""input_ids""", """attention_mask"""]





			def __init__(				self	:       Optional[Any]			,     lowercase	:       Union[str, Any]			,     lowercase	:       Dict="<s>"			,     lowercase	:       Optional[Any]="</s>"			,     lowercase	:       str="<unk>"			,     lowercase	:       Dict="<pad>"			,     lowercase	:       Tuple="<::::>"			,     lowercase	:       Optional[Dict[str, Any]] = None			,     **lowercase	:       List[str]			,     )						->					None:
									"""simple docstring"""







									__lowercase					=				{} if sp_model_kwargs is None else sp_model_kwargs

									# Add extra_ids to the special token list
									super().__init__(
									    bos_token=lowercase			,     eos_token=lowercase			,     unk_token=lowercase			,     pad_token=lowercase			,     sep_token=lowercase			,     sp_model_kwargs=self.sp_model_kwargs			,     **lowercase			,     )

									__lowercase					=				vocab_file

									__lowercase					=				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
									self.sp_model.Load(lowercase   )





			@property
			def 		snake_case__			(				self	:       Any   )						->					str:
									"""simple docstring"""







									return self.sp_model.get_piece_size()





			def 		snake_case__			(				self	:       Optional[int]   )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase					=				{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	:       Optional[Any]   )						->					Tuple:
									"""simple docstring"""







									__lowercase					=				self.__dict__.copy()
									__lowercase					=				None
									return state





			def __setstate__(				self	:       str			,     lowercase	:       Optional[int]   )						->					int:
									"""simple docstring"""







									__lowercase					=				d

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

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





			def 		snake_case__			(				self	:       Optional[int]			,     lowercase	:       str   )						->					List[str]:
									"""simple docstring"""







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





			def 		snake_case__			(				self	:       Tuple			,     lowercase	:       Tuple   )						->					Dict:
									"""simple docstring"""







									return self.sp_model.piece_to_id(lowercase   )





			def 		snake_case__			(				self	:       int			,     lowercase	:       int   )						->					str:
									"""simple docstring"""







									__lowercase					=				self.sp_model.IdToPiece(lowercase   )
									return token





			def 		snake_case__			(				self	:       List[Any]			,     lowercase	:       List[str]   )						->					Dict:
									"""simple docstring"""







									__lowercase					=				[]
									__lowercase					=				""""""
									for token in tokens:
															# make sure that special tokens are not decoded using sentencepiece model
															if token in self.all_special_tokens:
																					out_string += self.sp_model.decode(lowercase   ) + token
																					__lowercase					=				[]
															else:
																					current_sub_tokens.append(lowercase   )
									out_string += self.sp_model.decode(lowercase   )
									return out_string.strip()







			def 		snake_case__			(				self	:       Optional[int]			,     lowercase	:       str			,     lowercase	:       Optional[str] = None   )						->					Tuple[str]:
									"""simple docstring"""







									if not os.path.isdir(lowercase   ):
															logger.error(F"Vocabulary path ({save_directory}) should be a directory"   )
															return
									__lowercase					=				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   ) 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:
																					__lowercase					=				self.sp_model.serialized_model_proto()
																					fi.write(lowercase   )

									return (out_vocab_file,)










def  UpperCAmelCase__    (    lowercase__   ) ->      Optional[int]:
						__lowercase					=				len(lowercase__   )
						__lowercase					=				sum(lowercase__   )

						__lowercase					=				[[False for x in range(s + 1   )] for y in range(n + 1   )]

						for i in range(1						,       n + 1   ):
												__lowercase					=				True

						for i in range(1						,       s + 1   ):
												__lowercase					=				False

						for i in range(1						,       n + 1   ):
												for j in range(1						,       s + 1   ):
																		__lowercase					=				dp[i][j - 1]

																		if arr[i - 1] <= j:
																								__lowercase					=				dp[i][j] or dp[i - 1][j - arr[i - 1]]

						for j in range(int(s / 2   )						,       -1						,       -1   ):
												if dp[n][j] is True:
																		__lowercase					=				s - 2 * j
																		break

						return diff





