
import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


snake_case_      :					Optional[int]				      =     logging.get_logger(__name__)

snake_case_      :					str				      =     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

snake_case_      :					Optional[Any]				      =     {
    'vocab_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
        'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
        'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
        'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
        'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
        'microsoft/deberta-xlarge-mnli': (
            'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
        ),
    },
}

snake_case_      :					Optional[Any]				      =     {
    'microsoft/deberta-base': 5_1_2,
    'microsoft/deberta-large': 5_1_2,
    'microsoft/deberta-xlarge': 5_1_2,
    'microsoft/deberta-base-mnli': 5_1_2,
    'microsoft/deberta-large-mnli': 5_1_2,
    'microsoft/deberta-xlarge-mnli': 5_1_2,
}

snake_case_      :					Optional[int]				      =     {
    'microsoft/deberta-base': {'do_lower_case': False},
    'microsoft/deberta-large': {'do_lower_case': False},
}





class 		__lowerCamelCase     (   lowercase		):
							lowerCamelCase__:				Dict      =							VOCAB_FILES_NAMES
							lowerCamelCase__:				str      =							PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase__:				Tuple      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase__:				str      =							['''input_ids''', '''attention_mask''', '''token_type_ids''']
							lowerCamelCase__:				int      =							DebertaTokenizer



							def __init__(     self	,				__snake_case=None	,				__snake_case=None	,				__snake_case=None	,				__snake_case="replace"	,				__snake_case="[CLS]"	,				__snake_case="[SEP]"	,				__snake_case="[SEP]"	,				__snake_case="[CLS]"	,				__snake_case="[UNK]"	,				__snake_case="[PAD]"	,				__snake_case="[MASK]"	,				__snake_case=False	,				**__snake_case	,				)						->     Any:






								"""simple docstring"""



								super().__init__(
								    __snake_case	,				__snake_case	,				tokenizer_file=__snake_case	,				errors=__snake_case	,				bos_token=__snake_case	,				eos_token=__snake_case	,				unk_token=__snake_case	,				sep_token=__snake_case	,				cls_token=__snake_case	,				pad_token=__snake_case	,				mask_token=__snake_case	,				add_prefix_space=__snake_case	,				**__snake_case	,				)
								UpperCAmelCase:					Dict 						=     kwargs.pop("add_bos_token"	,				__snake_case							)

								UpperCAmelCase:					str 						=     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
								if pre_tok_state.get("add_prefix_space"	,				__snake_case							) != add_prefix_space:
									UpperCAmelCase:					str 						=     getattr(__snake_case	,				pre_tok_state.pop("type"							)							)
									UpperCAmelCase:					List[str] 						=     add_prefix_space
									UpperCAmelCase:					Tuple 						=     pre_tok_class(**__snake_case							)

								UpperCAmelCase:					str 						=     add_prefix_space



							@property
							def     A__ (     self							)						->     str:






								"""simple docstring"""



								if self._mask_token is None:
									if self.verbose:
										logger.error("Using mask_token, but it is not set yet."							)
									return None
								return str(self._mask_token							)



							@mask_token.setter
							def     A__ (     self	,				__snake_case							)						->     Union[str, Any]:






								"""simple docstring"""



								UpperCAmelCase:					Optional[Any] 						=     AddedToken(__snake_case	,				lstrip=__snake_case	,				rstrip=__snake_case							) if isinstance(__snake_case	,				__snake_case							) else value
								UpperCAmelCase:					List[Any] 						=     value



							def     A__ (     self	,				__snake_case	,				__snake_case = None							)						->     List[int]:






								"""simple docstring"""



								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     A__ (     self	,				__snake_case	,				__snake_case = None							)						->     List[int]:






								"""simple docstring"""



								UpperCAmelCase:					Dict 						=     [self.sep_token_id]
								UpperCAmelCase:					int 						=     [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	,				*__snake_case	,				**__snake_case							)						->     BatchEncoding:






								"""simple docstring"""



								UpperCAmelCase:					Dict 						=     kwargs.get("is_split_into_words"	,				__snake_case							)
								assert self.add_prefix_space or not is_split_into_words, (
								    F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
								    "to use it with pretokenized inputs."
								)

								return super()._batch_encode_plus(*__snake_case	,				**__snake_case							)



							def     A__ (     self	,				*__snake_case	,				**__snake_case							)						->     BatchEncoding:






								"""simple docstring"""



								UpperCAmelCase:					Any 						=     kwargs.get("is_split_into_words"	,				__snake_case							)

								assert self.add_prefix_space or not is_split_into_words, (
								    F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
								    "to use it with pretokenized inputs."
								)

								return super()._encode_plus(*__snake_case	,				**__snake_case							)



							def     A__ (     self	,				__snake_case	,				__snake_case = None							)						->     Tuple[str]:






								"""simple docstring"""



								UpperCAmelCase:					Optional[int] 						=     self._tokenizer.model.save(__snake_case	,				name=__snake_case							)
								return tuple(__snake_case							)




							def     A__ (     self	,				__snake_case							)						->     List[int]:






								"""simple docstring"""



								UpperCAmelCase:					List[Any] 						=     []
								for is_user, text in conversation.iter_texts():
									input_ids.extend(self.encode(__snake_case	,				add_special_tokens=__snake_case							) + [self.eos_token_id]							)

								if len(__snake_case							) > self.model_max_length:
									UpperCAmelCase:					Tuple 						=     input_ids[-self.model_max_length :]
								return input_ids


def      __UpperCAmelCase    (  snake_case_							:		str				):



	'''simple docstring'''



	UpperCAmelCase:					Tuple 						=     str(snake_case_				).strip()
	if not bin_string:
		raise ValueError("Empty string was passed to the function"				)
	UpperCAmelCase:					List[Any] 						=     bin_string[0] == "-"
	if is_negative:
		UpperCAmelCase:					Optional[int] 						=     bin_string[1:]
	if not all(char in "01" for char in bin_string				):
		raise ValueError("Non-binary value was passed to the function"				)
	UpperCAmelCase:					List[str] 						=     0
	for char in bin_string:
		UpperCAmelCase:					Union[str, Any] 						=     2 * decimal_number + int(snake_case_				)
	return -decimal_number if is_negative else decimal_number


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

	testmod()
