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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
							from .tokenization_rembert import RemBertTokenizer
else:
							UpperCamelCase_						:     Optional[int]	       =							None

UpperCamelCase_						:     Tuple	       =							logging.get_logger(__name__)
UpperCamelCase_						:     Tuple	       =							{"""vocab_file""": """sentencepiece.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase_						:     Union[str, Any]	       =							{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
    """tokenizer_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/tokenizer.json""",
    },
}

UpperCamelCase_						:     str	       =							{
    """google/rembert""": 256,
}

UpperCamelCase_						:     int	       =							"""▁"""




class   __lowercase						(						__snake_case       ):
	_A       =   VOCAB_FILES_NAMES
	_A       =   PRETRAINED_VOCAB_FILES_MAP
	_A       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       =   RemBertTokenizer






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

							super().__init__(
							    snake_case      ,	tokenizer_file=snake_case      ,	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      ,	)

							_lowercase       :	List[Any]           =   do_lower_case
							_lowercase       :	Optional[Any]           =   remove_space
							_lowercase       :	Dict           =   keep_accents
							_lowercase       :	Any           =   vocab_file
							_lowercase       :	Optional[int]           =   False if not self.vocab_file else True






	def       _a(self				: List[str]      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None    ) ->			List[int]:
							_lowercase       :	int           =   [self.sep_token_id]
							_lowercase       :	Optional[Any]           =   [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				: Union[str, Any]      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None      ,	snake_case				: bool = False    ) ->			List[int]:

							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				: str      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None    ) ->			List[int]:
							_lowercase       :	str           =   [self.sep_token_id]
							_lowercase       :	Optional[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    ) * [0] + len(token_ids_a + sep    ) * [1]






	def       _a(self				: List[Any]      ,	snake_case				: str      ,	snake_case				: Optional[str] = None    ) ->			Tuple[str]:
							if not os.path.isdir(snake_case    ):
													logger.error("Vocabulary path ({}) should be a directory".format(snake_case    )    )
													return
							_lowercase       :	Tuple           =   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,)






import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union




@dataclass
class   __lowercase						:
	_A       =   None
	_A       =   False
	_A       =   False
	_A       =   False
	_A       =   None
	_A       =   None
	_A       =   False
	_A       =   False
	_A       =   False
	_A       =   True
	_A       =   None
	_A       =   1
	_A       =   None
	_A       =   False
	_A       =   None
	_A       =   None






	def       _a(self				: str    ) ->			"DownloadConfig":
							return self.__class__(**{k: copy.deepcopy(snake_case    ) for k, v in self.__dict__.items()}    )




