






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

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
							from .tokenization_deberta_va import DebertaVaTokenizer
else:
							a		:	List[Any]      					=			None

a		:	Union[str, Any]      					=			logging.get_logger(__name__)

a		:	Union[str, Any]      					=			{"vocab_file": "spm.model", "tokenizer_file": "tokenizer.json"}

a		:	Optional[Any]      					=			{
    "vocab_file": {
        "microsoft/deberta-v2-xlarge": "https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xxlarge": "https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model"
        ),
        "microsoft/deberta-v2-xxlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model"
        ),
    }
}

a		:	str      					=			{
    "microsoft/deberta-v2-xlarge": 512,
    "microsoft/deberta-v2-xxlarge": 512,
    "microsoft/deberta-v2-xlarge-mnli": 512,
    "microsoft/deberta-v2-xxlarge-mnli": 512,
}

a		:	str      					=			{
    "microsoft/deberta-v2-xlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xlarge-mnli": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge-mnli": {"do_lower_case": False},
}
class    a   (			_UpperCAmelCase       ):



						"""simple docstring"""


						a  :			Optional[Any]								=     VOCAB_FILES_NAMES
						a  :			str								=     PRETRAINED_VOCAB_FILES_MAP
						a  :			int								=     PRETRAINED_INIT_CONFIGURATION
						a  :			List[Any]								=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						a  :			List[Any]								=     DebertaVaTokenizer
						def __init__(				self :      int		,				__lowercase :      Any=None		,				__lowercase :      Dict=None		,				__lowercase :      Dict=False		,				__lowercase :      List[Any]=False		,				__lowercase :      List[Any]="[CLS]"		,				__lowercase :      Optional[Any]="[SEP]"		,				__lowercase :      str="[UNK]"		,				__lowercase :      List[Any]="[SEP]"		,				__lowercase :      Tuple="[PAD]"		,				__lowercase :      List[Any]="[CLS]"		,				__lowercase :      List[Any]="[MASK]"		,				**__lowercase :      List[Any]		,				)							->				Optional[Any]:
								super().__init__(
								    lowercase__		,				tokenizer_file=lowercase__		,				do_lower_case=lowercase__		,				bos_token=lowercase__		,				eos_token=lowercase__		,				unk_token=lowercase__		,				sep_token=lowercase__		,				pad_token=lowercase__		,				cls_token=lowercase__		,				mask_token=lowercase__		,				split_by_punct=lowercase__		,				**lowercase__		,				)

								__UpperCAmelCase							:     List[str]									=  do_lower_case
								__UpperCAmelCase							:     List[Any]									=  split_by_punct
								__UpperCAmelCase							:     int									=  vocab_file
								__UpperCAmelCase							:     List[str]									=  False if not self.vocab_file else True
						def      UpperCAmelCase				(				self :      Union[str, Any]		,				__lowercase :      str		,				__lowercase :      Dict=None )							->				str:






								if token_ids_a is None:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								__UpperCAmelCase							:     Any									=  [self.cls_token_id]
								__UpperCAmelCase							:     str									=  [self.sep_token_id]
								return cls + token_ids_a + sep + token_ids_a + sep
						def      UpperCAmelCase				(				self :      str		,				__lowercase :      List[str]		,				__lowercase :      int=None		,				__lowercase :      Optional[Any]=False )							->				Any:






								if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=lowercase__		,				token_ids_a=lowercase__		,				already_has_special_tokens=lowercase__ )

								if token_ids_a is not None:
										return [1] + ([0] * len(lowercase__ )) + [1] + ([0] * len(lowercase__ )) + [1]
								return [1] + ([0] * len(lowercase__ )) + [1]
						def      UpperCAmelCase				(				self :      List[Any]		,				__lowercase :      List[str]		,				__lowercase :      Tuple=None )							->				Union[str, Any]:
								__UpperCAmelCase							:     Dict									=  [self.sep_token_id]
								__UpperCAmelCase							:     Union[str, 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      UpperCAmelCase				(				self :      int		,				__lowercase :      Any		,				__lowercase :      Any = None )							->				List[str]:






								if not self.can_save_slow_tokenizer:
										raise ValueError(
										    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
										    """tokenizer.""" )

								if not os.path.isdir(lowercase__ ):
										logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
										return
								__UpperCAmelCase							:     Dict									=  os.path.join(
								    lowercase__		,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

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

								return (out_vocab_file,)










def     lowerCamelCase__				(   __lowerCamelCase      :					list		):
  if len(__lowerCamelCase		) <= 1:
    return data
  else:
    return [
        *quick_sort([e for e in data[1:] if e <= data[0]]		),
        data[0],
        *quick_sort([e for e in data[1:] if e > data[0]]		),
    ]


if __name__ == "__main__":
       import doctest

       doctest.testmod()


