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


A__           =							logging.get_logger(__name__)

A__           =							{"""vocab_file""": """sentencepiece.model"""}

A__           =							{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
}

A__           =							{
    """google/rembert""": 256,
}
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     VOCAB_FILES_NAMES
							_UpperCAmelCase						    =     PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase						    =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES







							def __init__(				self     :    str	,					__snake_case     :    Any	,					__snake_case     :    int=False	,					__snake_case     :    Optional[int]=True	,					__snake_case     :    List[Any]=True	,					__snake_case     :    Any="[CLS]"	,					__snake_case     :    Optional[int]="[SEP]"	,					__snake_case     :    int="[UNK]"	,					__snake_case     :    Optional[int]="[SEP]"	,					__snake_case     :    Any="[PAD]"	,					__snake_case     :    int="[CLS]"	,					__snake_case     :    Any="[MASK]"	,					**__snake_case     :    int	,					):
										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	,					)

										lowerCamelCase						:Dict						  =     do_lower_case
										lowerCamelCase						:Union[str, Any]						  =     remove_space
										lowerCamelCase						:Tuple						  =     keep_accents
										lowerCamelCase						:Optional[Any]						  =     vocab_file

										lowerCamelCase						:Any						  =     spm.SentencePieceProcessor()
										self.sp_model.Load(__snake_case		)







							@property
							def 				snake_case  (				self     :    Dict		):
										return len(self.sp_model		)







							def 				snake_case  (				self     :    List[str]		):
										lowerCamelCase						:str						  =     {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     :    Optional[Any]		):
										lowerCamelCase						:Optional[int]						  =     self.__dict__.copy()
										lowerCamelCase						:Optional[int]						  =     None
										return state







							def __setstate__(				self     :    List[str]	,					__snake_case     :    Optional[Any]		):
										lowerCamelCase						:Optional[Any]						  =     d
										lowerCamelCase						:Any						  =     spm.SentencePieceProcessor()
										self.sp_model.Load(self.vocab_file		)







							def 				snake_case  (				self     :    Optional[int]	,					__snake_case     :    Optional[Any]	,					__snake_case     :    List[Any]=False		):
										lowerCamelCase						:Dict						  =     self.sp_model.EncodeAsPieces(__snake_case		)
										return pieces







							def 				snake_case  (				self     :    str	,					__snake_case     :    int		):
										return self.sp_model.PieceToId(__snake_case		)







							def 				snake_case  (				self     :    List[Any]	,					__snake_case     :    Union[str, Any]		):
										return self.sp_model.IdToPiece(__snake_case		)







							def 				snake_case  (				self     :    List[str]	,					__snake_case     :    List[str]		):
										lowerCamelCase						:Optional[int]						  =     self.sp_model.decode_pieces(__snake_case		)
										return out_string







							def 				snake_case  (				self     :    Union[str, Any]	,					__snake_case     :    List[int]	,					__snake_case     :    Optional[List[int]] = None		):
										lowerCamelCase						:List[str]						  =     [self.sep_token_id]
										lowerCamelCase						:str						  =     [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 				snake_case  (				self     :    int	,					__snake_case     :    List[int]	,					__snake_case     :    Optional[List[int]] = None	,					__snake_case     :    bool = 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 				snake_case  (				self     :    Dict	,					__snake_case     :    List[int]	,					__snake_case     :    Optional[List[int]] = None		):
										lowerCamelCase						:int						  =     [self.sep_token_id]
										lowerCamelCase						: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 				snake_case  (				self     :    str	,					__snake_case     :    str	,					__snake_case     :    Optional[str] = None		):
										if not os.path.isdir(__snake_case		):
													logger.error('''Vocabulary path ({}) should be a directory'''.format(__snake_case		)		)
													return
										lowerCamelCase						:Dict						  =     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 collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A__           =							logging.get_logger(__name__)

A__           =							{
    """andreasmadsen/efficient_mlm_m0.40""": (
        """https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"""
    ),
}
class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase						    =     'roberta-prelayernorm'







							def __init__(				self     :    str	,					__snake_case     :    List[str]=50265	,					__snake_case     :    Union[str, Any]=768	,					__snake_case     :    Tuple=12	,					__snake_case     :    int=12	,					__snake_case     :    Any=3072	,					__snake_case     :    Optional[int]="gelu"	,					__snake_case     :    List[Any]=0.1	,					__snake_case     :    int=0.1	,					__snake_case     :    Union[str, Any]=512	,					__snake_case     :    Dict=2	,					__snake_case     :    int=0.0_2	,					__snake_case     :    Any=1e-1_2	,					__snake_case     :    Optional[int]=1	,					__snake_case     :    Dict=0	,					__snake_case     :    Optional[int]=2	,					__snake_case     :    Any="absolute"	,					__snake_case     :    Union[str, Any]=True	,					__snake_case     :    List[str]=None	,					**__snake_case     :    Optional[int]	,					):
										super().__init__(pad_token_id=__snake_case	,					bos_token_id=__snake_case	,					eos_token_id=__snake_case	,					**__snake_case		)

										lowerCamelCase						:Optional[int]						  =     vocab_size
										lowerCamelCase						:Dict						  =     hidden_size
										lowerCamelCase						:Tuple						  =     num_hidden_layers
										lowerCamelCase						:Optional[int]						  =     num_attention_heads
										lowerCamelCase						:Any						  =     hidden_act
										lowerCamelCase						:List[Any]						  =     intermediate_size
										lowerCamelCase						:Union[str, Any]						  =     hidden_dropout_prob
										lowerCamelCase						:str						  =     attention_probs_dropout_prob
										lowerCamelCase						:Tuple						  =     max_position_embeddings
										lowerCamelCase						:int						  =     type_vocab_size
										lowerCamelCase						:Optional[Any]						  =     initializer_range
										lowerCamelCase						:Union[str, Any]						  =     layer_norm_eps
										lowerCamelCase						:Dict						  =     position_embedding_type
										lowerCamelCase						:List[Any]						  =     use_cache
										lowerCamelCase						:Optional[int]						  =     classifier_dropout


class   _lowerCAmelCase		(     __SCREAMING_SNAKE_CASE				):







							@property
							def 				snake_case  (				self     :    Any		):
										if self.task == "multiple-choice":
													lowerCamelCase						:Optional[Any]						  =     {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
										else:
													lowerCamelCase						:List[str]						  =     {0: '''batch''', 1: '''sequence'''}
										return OrderedDict(
										    [
										        ('''input_ids''', dynamic_axis),
										        ('''attention_mask''', dynamic_axis),
										    ]		)



