

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


_UpperCAmelCase		:       Optional[int]						    =	logging.get_logger(__name__)

_UpperCAmelCase		:       Union[str, Any]						    =	{"""vocab_file""": """sentencepiece.model"""}

_UpperCAmelCase		:       List[Any]						    =	{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
}

_UpperCAmelCase		:       Optional[Any]						    =	{
    """google/rembert""": 256,
}







class 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			Tuple	      =      VOCAB_FILES_NAMES
				__SCREAMING_SNAKE_CASE :			List[str]	      =      PRETRAINED_VOCAB_FILES_MAP
				__SCREAMING_SNAKE_CASE :			str	      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




				def __init__( self				,       snake_case				,       snake_case=False				,       snake_case=True				,       snake_case=True				,       snake_case="[CLS]"				,       snake_case="[SEP]"				,       snake_case="[UNK]"				,       snake_case="[SEP]"				,       snake_case="[PAD]"				,       snake_case="[CLS]"				,       snake_case="[MASK]"				,       **snake_case				,       ):
											super().__init__(
											    do_lower_case=snake_case				,       remove_space=snake_case				,       keep_accents=snake_case				,       bos_token=snake_case				,       eos_token=snake_case				,       unk_token=snake_case				,       sep_token=snake_case				,       pad_token=snake_case				,       cls_token=snake_case				,       mask_token=snake_case				,       **snake_case				,       )

											snake_case_          =   do_lower_case
											snake_case_          =   remove_space
											snake_case_          =   keep_accents
											snake_case_          =   vocab_file

											snake_case_          =   spm.SentencePieceProcessor()
											self.sp_model.Load(snake_case	)




				@property
				def    a							( self	):
											return len(self.sp_model	)




				def    a							( self	):
											snake_case_          =   {self.convert_ids_to_tokens(snake_case	): i for i in range(self.vocab_size	)}
											vocab.update(self.added_tokens_encoder	)
											return vocab




				def __getstate__( self	):
											snake_case_          =   self.__dict__.copy()
											snake_case_          =   None
											return state




				def __setstate__( self				,       snake_case	):
											snake_case_          =   d
											snake_case_          =   spm.SentencePieceProcessor()
											self.sp_model.Load(self.vocab_file	)




				def    a							( self				,       snake_case				,       snake_case=False	):
											snake_case_          =   self.sp_model.EncodeAsPieces(snake_case	)
											return pieces




				def    a							( self				,       snake_case	):
											return self.sp_model.PieceToId(snake_case	)




				def    a							( self				,       snake_case	):
											return self.sp_model.IdToPiece(snake_case	)




				def    a							( self				,       snake_case	):
											snake_case_          =   self.sp_model.decode_pieces(snake_case	)
											return out_string




				def    a							( self				,       snake_case				,       snake_case = None	):
											snake_case_          =   [self.sep_token_id]
											snake_case_          =   [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    a							( self				,       snake_case				,       snake_case = None				,       snake_case = False	):

											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(snake_case	)) + [1] + ([0] * len(snake_case	)) + [1]
											return [1] + ([0] * len(snake_case	)) + [1]




				def    a							( self				,       snake_case				,       snake_case = None	):
											snake_case_          =   [self.sep_token_id]
											snake_case_          =   [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    a							( self				,       snake_case				,       snake_case = None	):
											if not os.path.isdir(snake_case	):
																		logger.error('Vocabulary path ({}) should be a directory'.format(snake_case	)	)
																		return
											snake_case_          =   os.path.join(
											    snake_case				,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

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

											return (out_vocab_file,)







from __future__ import annotations





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   []
							create_all_state(1       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							[]       ,							UpperCamelCase__				)
							return result





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							):







							'''simple docstring'''






							if level == 0:
														total_list.append(current_list[:]				)
														return

							for i in range(UpperCamelCase__       ,							total_number - level + 2				):
														current_list.append(UpperCamelCase__				)
														create_all_state(i + 1       ,							UpperCamelCase__       ,							level - 1       ,							UpperCamelCase__       ,							UpperCamelCase__				)
														current_list.pop()





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							for i in total_list:
														print(*UpperCamelCase__				)


if __name__ == "__main__":
					_UpperCAmelCase		:       str						    =	4
					_UpperCAmelCase		:       Tuple						    =	2
					_UpperCAmelCase		:       Optional[int]						    =	generate_all_combinations(n, k)
					print_all_state(total_list)




