




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__			:       Dict         =							None

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

lowerCamelCase__			:       List[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',
    },
}

lowerCamelCase__			:       Optional[Any]         =							{
    'google/rembert': 256,
}

lowerCamelCase__			:       List[Any]         =							'▁'





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   VOCAB_FILES_NAMES
 lowercase_       =   PRETRAINED_VOCAB_FILES_MAP
 lowercase_       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_       =   RemBertTokenizer



 def __init__(							self  :		Dict    ,    _lowerCAmelCase  :		Any=None    ,    _lowerCAmelCase  :		List[str]=None    ,    _lowerCAmelCase  :		List[str]=True    ,    _lowerCAmelCase  :		Optional[Any]=True    ,    _lowerCAmelCase  :		Any=False    ,    _lowerCAmelCase  :		Optional[Any]="[CLS]"    ,    _lowerCAmelCase  :		Union[str, Any]="[SEP]"    ,    _lowerCAmelCase  :		Tuple="<unk>"    ,    _lowerCAmelCase  :		Optional[Any]="[SEP]"    ,    _lowerCAmelCase  :		Optional[Any]="<pad>"    ,    _lowerCAmelCase  :		List[str]="[CLS]"    ,    _lowerCAmelCase  :		int="[MASK]"    ,    **_lowerCAmelCase  :		List[str]    ,    ):
       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE_     						=      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    ,    )

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



 def 				lowerCAmelCase_  (							self  :		Optional[Any]    ,    _lowerCAmelCase  :		List[int]    ,    _lowerCAmelCase  :		Optional[List[int]] = None						):
       SCREAMING_SNAKE_CASE_     						=      [self.sep_token_id]
       SCREAMING_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 				lowerCAmelCase_  (							self  :		Tuple    ,    _lowerCAmelCase  :		List[int]    ,    _lowerCAmelCase  :		Optional[List[int]] = None    ,    _lowerCAmelCase  :		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(_lowerCAmelCase						)) + [1] + ([0] * len(_lowerCAmelCase						)) + [1]
       return [1] + ([0] * len(_lowerCAmelCase						)) + [1]



 def 				lowerCAmelCase_  (							self  :		Tuple    ,    _lowerCAmelCase  :		List[int]    ,    _lowerCAmelCase  :		Optional[List[int]] = None						):
       SCREAMING_SNAKE_CASE_     						=      [self.sep_token_id]
       SCREAMING_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 				lowerCAmelCase_  (							self  :		Tuple    ,    _lowerCAmelCase  :		str    ,    _lowerCAmelCase  :		Optional[str] = None						):
       if not os.path.isdir(_lowerCAmelCase						):
             logger.error('Vocabulary path ({}) should be a directory'.format(_lowerCAmelCase						)						)
             return
       SCREAMING_SNAKE_CASE_     						=      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,)





from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
   import accelerate

def  UpperCAmelCase_							(				__UpperCAmelCase						:     Optional[int]							) ->			int:
      if not is_accelerate_available():
            return method
      SCREAMING_SNAKE_CASE_     						=      version.parse(accelerate.__version__							).base_version
      if version.parse(__UpperCAmelCase							) < version.parse('0.17.0'							):
            return method

      def wrapper(self						:     Optional[int]      ,      *__UpperCAmelCase						:     Optional[Any]      ,      **__UpperCAmelCase						:     Optional[Any]							):
            if hasattr(self      ,      '_hf_hook'							) and hasattr(self._hf_hook      ,      'pre_forward'							):
                  self._hf_hook.pre_forward(self							)
            return method(self      ,      *__UpperCAmelCase      ,      **__UpperCAmelCase							)

      return wrapper