






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


A__      :     List[Any]       =					logging.get_logger(__name__)

A__      :     Optional[int]       =					{'vocab_file': 'spiece.model'}

A__      :     Union[str, Any]       =					{
    'vocab_file': {
        'bert_for_seq_generation': (
            'https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'
        ),
    }
}

A__      :     List[Any]       =					{'bert_for_seq_generation': 5_12}
class  _UpperCAmelCase   (			A__      ):

				"""simple docstring"""




				lowercase__											=			VOCAB_FILES_NAMES
				lowercase__											=			PRETRAINED_VOCAB_FILES_MAP
				lowercase__											=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowercase__											=			[]
				lowercase__											=			["""input_ids""", """attention_mask"""]




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

								'''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=lowerCamelCase,    eos_token=lowerCamelCase,    unk_token=lowerCamelCase,    pad_token=lowerCamelCase,    sep_token=lowerCamelCase,    sp_model_kwargs=self.sp_model_kwargs,    **lowerCamelCase,    )

								lowercase__  					=     vocab_file

								lowercase__  					=     spm.SentencePieceProcessor(**self.sp_model_kwargs    )
								self.sp_model.Load(lowerCamelCase    )




				@property
				def 							lowercase__  (	self		:       Dict    ):

								'''simple docstring'''
								return self.sp_model.get_piece_size()




				def 							lowercase__  (	self		:       Union[str, Any]    ):

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




				def __getstate__(	self		:       Optional[Any]    ):

								'''simple docstring'''
								lowercase__  					=     self.__dict__.copy()
								lowercase__  					=     None
								return state




				def __setstate__(	self		:       Union[str, Any],    lowerCamelCase		:       Dict    ):

								'''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 							lowercase__  (	self		:       Optional[int],    lowerCamelCase		:       str    ):

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




				def 							lowercase__  (	self		:       int,    lowerCamelCase		:       List[Any]    ):

								'''simple docstring'''
								return self.sp_model.piece_to_id(lowerCamelCase    )




				def 							lowercase__  (	self		:       int,    lowerCamelCase		:       Tuple    ):

								'''simple docstring'''
								lowercase__  					=     self.sp_model.IdToPiece(lowerCamelCase    )
								return token




				def 							lowercase__  (	self		:       List[str],    lowerCamelCase		:       str    ):

								'''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(lowerCamelCase    ) + token
																lowercase__  					=     []
												else:
																current_sub_tokens.append(lowerCamelCase    )
								out_string += self.sp_model.decode(lowerCamelCase    )
								return out_string.strip()




				def 							lowercase__  (	self		:       List[str],    lowerCamelCase		:       str,    lowerCamelCase		:       Optional[str] = None    ):

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

								return (out_vocab_file,)












from __future__ import annotations

from typing import Any






def     a     (		lowerCamelCase_							):






				'''simple docstring'''
				if not postfix_notation:
								return 0

				lowercase__  					=     {'''+''', '''-''', '''*''', '''/'''}
				lowercase__  					=     []

				for token in postfix_notation:
								if token in operations:
												lowercase__					,		lowercase__  					=     stack.pop(), stack.pop()
												if token == "+":
																stack.append(a + b							)
												elif token == "-":
																stack.append(a - b							)
												elif token == "*":
																stack.append(a * b							)
												else:
																if a * b < 0 and a % b != 0:
																				stack.append(a // b + 1							)
																else:
																				stack.append(a // b							)
								else:
												stack.append(int(lowerCamelCase_							)							)

				return stack.pop()


if __name__ == "__main__":
							import doctest

							doctest.testmod()




