
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:
							lowercase__						:List[Any]					    =       None

lowercase__						:int					    =       logging.get_logger(__name__)

lowercase__						:Any					    =       {"vocab_file": "spm.model", "tokenizer_file": "tokenizer.json"}

lowercase__						:str					    =       {
    "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"
        ),
    }
}

lowercase__						:Union[str, Any]					    =       {
    "microsoft/deberta-v2-xlarge": 512,
    "microsoft/deberta-v2-xxlarge": 512,
    "microsoft/deberta-v2-xlarge-mnli": 512,
    "microsoft/deberta-v2-xxlarge-mnli": 512,
}

lowercase__						:Any					    =       {
    "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 							lowercase						(   _a						):
							lowercase_			:			Dict			   =VOCAB_FILES_NAMES
							lowercase_			:			Dict			   =PRETRAINED_VOCAB_FILES_MAP
							lowercase_			:			Optional[Any]			   =PRETRAINED_INIT_CONFIGURATION
							lowercase_			:			List[str]			   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_			:			Union[str, Any]			   =DebertaVaTokenizer




							def __init__(							self  ,A__=None  ,A__=None  ,A__=False  ,A__=False  ,A__="[CLS]"  ,A__="[SEP]"  ,A__="[UNK]"  ,A__="[SEP]"  ,A__="[PAD]"  ,A__="[CLS]"  ,A__="[MASK]"  ,**A__  ,):
												super().__init__(
												    _SCREAMING_SNAKE_CASE  ,tokenizer_file=_SCREAMING_SNAKE_CASE  ,do_lower_case=_SCREAMING_SNAKE_CASE  ,bos_token=_SCREAMING_SNAKE_CASE  ,eos_token=_SCREAMING_SNAKE_CASE  ,unk_token=_SCREAMING_SNAKE_CASE  ,sep_token=_SCREAMING_SNAKE_CASE  ,pad_token=_SCREAMING_SNAKE_CASE  ,cls_token=_SCREAMING_SNAKE_CASE  ,mask_token=_SCREAMING_SNAKE_CASE  ,split_by_punct=_SCREAMING_SNAKE_CASE  ,**_SCREAMING_SNAKE_CASE  ,)

												lowercase		      =		do_lower_case
												lowercase		      =		split_by_punct
												lowercase		      =		vocab_file
												lowercase		      =		False if not self.vocab_file else True




							def 					A__ (							self  ,A__  ,A__=None):






												if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												lowercase		      =		[self.cls_token_id]
												lowercase		      =		[self.sep_token_id]
												return cls + token_ids_a + sep + token_ids_a + sep




							def 					A__ (							self  ,A__  ,A__=None  ,A__=False):






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

												if token_ids_a is not None:
																	return [1] + ([0] * len(_SCREAMING_SNAKE_CASE)) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE)) + [1]
												return [1] + ([0] * len(_SCREAMING_SNAKE_CASE)) + [1]




							def 					A__ (							self  ,A__  ,A__=None):
												lowercase		      =		[self.sep_token_id]
												lowercase		      =		[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  ,A__  ,A__ = None):






												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(_SCREAMING_SNAKE_CASE):
																	logger.error(f'Vocabulary path ({save_directory}) should be a directory')
																	return
												lowercase		      =		os.path.join(
												    _SCREAMING_SNAKE_CASE  ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

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

												return (out_vocab_file,)






'''simple docstring'''


__SCREAMING_SNAKE_CASE						=      {hex(i)[2:]: i for i in range(16)}  # Use [:2] to strip off the leading '0x'
def 					__magic_name__(       UpperCAmelCase__ :       str	):
						UpperCamelCase_     :	str					     =     hex_string.strip().lower()
						if not hex_string:
												raise ValueError("""Empty string was passed to the function"""	)
						UpperCamelCase_     :	Dict					     =     hex_string[0] == """-"""
						if is_negative:
												UpperCamelCase_     :	List[str]					     =     hex_string[1:]
						if not all(char in hex_table for char in hex_string	):
												raise ValueError("""Non-hexadecimal value was passed to the function"""	)
						UpperCamelCase_     :	int					     =     0
						for char in hex_string:
												UpperCamelCase_     :	Any					     =     16 * decimal_number + hex_table[char]
						return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
	from doctest import testmod

	testmod()




