





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:
					_lowerCamelCase						:     Union[str, Any]		   =	None

_lowerCamelCase						:     List[Any]		   =	logging.get_logger(__name__)
_lowerCamelCase						:     Union[str, Any]		   =	{'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

_lowerCamelCase						:     Optional[int]		   =	{
    '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',
    },
}

_lowerCamelCase						:     Dict		   =	{
    'google/rembert': 256,
}

_lowerCamelCase						:     Tuple		   =	'▁'

class       snake_case__						(		__snake_case							):






							'''simple docstring'''



							__A     =							VOCAB_FILES_NAMES
							__A     =							PRETRAINED_VOCAB_FILES_MAP
							__A     =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__A     =							RemBertTokenizer


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

												super().__init__(
												    lowerCAmelCase_					,			tokenizer_file=lowerCAmelCase_					,			do_lower_case=lowerCAmelCase_					,			remove_space=lowerCAmelCase_					,			keep_accents=lowerCAmelCase_					,			bos_token=lowerCAmelCase_					,			eos_token=lowerCAmelCase_					,			unk_token=lowerCAmelCase_					,			sep_token=lowerCAmelCase_					,			pad_token=lowerCAmelCase_					,			cls_token=lowerCAmelCase_					,			mask_token=lowerCAmelCase_					,			**lowerCAmelCase_					,			)

												UpperCAmelCase_		=  do_lower_case
												UpperCAmelCase_		=  remove_space
												UpperCAmelCase_		=  keep_accents
												UpperCAmelCase_		=  vocab_file
												UpperCAmelCase_		=  False if not self.vocab_file else True


							def 							UpperCamelCase      (       self  :       List[Any]					,			lowerCAmelCase_  :       List[Any]					,			lowerCAmelCase_  :       int = None   )       ->		Tuple:
												UpperCAmelCase_		=  [self.sep_token_id]
												UpperCAmelCase_		=  [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 							UpperCamelCase      (       self  :       Any					,			lowerCAmelCase_  :       Any					,			lowerCAmelCase_  :       Dict = None					,			lowerCAmelCase_  :       str = False   )       ->		Any:

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


							def 							UpperCamelCase      (       self  :       List[Any]					,			lowerCAmelCase_  :       Dict					,			lowerCAmelCase_  :       Dict = None   )       ->		Any:
												UpperCAmelCase_		=  [self.sep_token_id]
												UpperCAmelCase_		=  [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 							UpperCamelCase      (       self  :       Dict					,			lowerCAmelCase_  :       str					,			lowerCAmelCase_  :       Tuple = None   )       ->		Dict:
												if not os.path.isdir(lowerCAmelCase_   ):
																	logger.error('''Vocabulary path ({}) should be a directory'''.format(lowerCAmelCase_   )   )
																	return
												UpperCAmelCase_		=  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_   ):
																	copyfile(self.vocab_file					,			lowerCAmelCase_   )

												return (out_vocab_file,)






"""simple docstring"""






from diffusers.utils.testing_utils import require_onnxruntime






@require_onnxruntime
class lowerCAmelCase__      :






			'''simple docstring'''



			pass