

"""simple docstring"""

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


a__ :	List[Any]						= logging.get_logger(__name__)

a__ :	Union[str, Any]						= {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

a__ :	int						= {
    """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"""
        ),
    },
}

a__ :	List[str]						= {
    """microsoft/deberta-base""": 512,
    """microsoft/deberta-large""": 512,
    """microsoft/deberta-xlarge""": 512,
    """microsoft/deberta-base-mnli""": 512,
    """microsoft/deberta-large-mnli""": 512,
    """microsoft/deberta-xlarge-mnli""": 512,
}

a__ :	Dict						= {
    """microsoft/deberta-base""": {"""do_lower_case""": False},
    """microsoft/deberta-large""": {"""do_lower_case""": False},
}


class 			_snake_case     (						UpperCamelCase       ):
						__snake_case 			=     VOCAB_FILES_NAMES
						__snake_case 			=     PRETRAINED_VOCAB_FILES_MAP
						__snake_case 			=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__snake_case 			=     ['input_ids', 'attention_mask', 'token_type_ids']
						__snake_case 			=     DebertaTokenizer







						def __init__(self     ,							UpperCAmelCase_=None     ,							UpperCAmelCase_=None     ,							UpperCAmelCase_=None     ,							UpperCAmelCase_="replace"     ,							UpperCAmelCase_="[CLS]"     ,							UpperCAmelCase_="[SEP]"     ,							UpperCAmelCase_="[SEP]"     ,							UpperCAmelCase_="[CLS]"     ,							UpperCAmelCase_="[UNK]"     ,							UpperCAmelCase_="[PAD]"     ,							UpperCAmelCase_="[MASK]"     ,							UpperCAmelCase_=False     ,							**UpperCAmelCase_     ,							)			->						Union[str, Any]:
											super().__init__(
											    UpperCAmelCase_     ,							UpperCAmelCase_     ,							tokenizer_file=UpperCAmelCase_     ,							errors=UpperCAmelCase_     ,							bos_token=UpperCAmelCase_     ,							eos_token=UpperCAmelCase_     ,							unk_token=UpperCAmelCase_     ,							sep_token=UpperCAmelCase_     ,							cls_token=UpperCAmelCase_     ,							pad_token=UpperCAmelCase_     ,							mask_token=UpperCAmelCase_     ,							add_prefix_space=UpperCAmelCase_     ,							**UpperCAmelCase_     ,							)
											__lowercase												=			kwargs.pop('''add_bos_token'''     ,							UpperCAmelCase_							)

											__lowercase												=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
											if pre_tok_state.get('''add_prefix_space'''     ,							UpperCAmelCase_							) != add_prefix_space:
																__lowercase												=			getattr(UpperCAmelCase_     ,							pre_tok_state.pop('''type'''							)							)
																__lowercase												=			add_prefix_space
																__lowercase												=			pre_tok_class(**UpperCAmelCase_							)

											__lowercase												=			add_prefix_space







						@property
						def        _UpperCamelCase    (self							)			->						str:
											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        _UpperCamelCase    (self     ,							UpperCAmelCase_							)			->						Optional[int]:
											__lowercase												=			AddedToken(UpperCAmelCase_     ,							lstrip=UpperCAmelCase_     ,							rstrip=UpperCAmelCase_							) if isinstance(UpperCAmelCase_     ,							UpperCAmelCase_							) else value
											__lowercase												=			value







						def        _UpperCamelCase    (self     ,							UpperCAmelCase_     ,							UpperCAmelCase_ = None							)			->						List[int]:
											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        _UpperCamelCase    (self     ,							UpperCAmelCase_     ,							UpperCAmelCase_ = None							)			->						List[int]:
											__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        _UpperCamelCase    (self     ,							*UpperCAmelCase_     ,							**UpperCAmelCase_							)			->						BatchEncoding:
											__lowercase												=			kwargs.get('''is_split_into_words'''     ,							UpperCAmelCase_							)
											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(*UpperCAmelCase_     ,							**UpperCAmelCase_							)







						def        _UpperCamelCase    (self     ,							*UpperCAmelCase_     ,							**UpperCAmelCase_							)			->						BatchEncoding:
											__lowercase												=			kwargs.get('''is_split_into_words'''     ,							UpperCAmelCase_							)

											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(*UpperCAmelCase_     ,							**UpperCAmelCase_							)







						def        _UpperCamelCase    (self     ,							UpperCAmelCase_     ,							UpperCAmelCase_ = None							)			->						Tuple[str]:
											__lowercase												=			self._tokenizer.model.save(UpperCAmelCase_     ,							name=UpperCAmelCase_							)
											return tuple(UpperCAmelCase_							)







						def        _UpperCamelCase    (self     ,							UpperCAmelCase_							)			->						List[int]:
											__lowercase												=			[]
											for is_user, text in conversation.iter_texts():
																input_ids.extend(self.encode(UpperCAmelCase_     ,							add_special_tokens=UpperCAmelCase_							) + [self.eos_token_id]							)

											if len(UpperCAmelCase_							) > self.model_max_length:
																__lowercase												=			input_ids[-self.model_max_length :]
											return input_ids





"""simple docstring"""

def 				__UpperCamelCase   (    a__: int ,	a__: int = 10_00			)				->			str:




					"""simple docstring"""



					if (not isinstance(a__ ,	a__			)) or (digit_position <= 0):
										raise ValueError('''Digit position must be a positive integer'''			)
					elif (not isinstance(a__ ,	a__			)) or (precision < 0):
										raise ValueError('''Precision must be a nonnegative integer'''			)

					# compute an approximation of (16 ** (n - 1)) * pi whose fractional part is mostly
					# accurate
					__lowercase												=			(
					    4 * _subsum(a__ ,	1 ,	a__			)
					    - 2 * _subsum(a__ ,	4 ,	a__			)
					    - _subsum(a__ ,	5 ,	a__			)
					    - _subsum(a__ ,	6 ,	a__			)
					)

					# return the first hex digit of the fractional part of the result
					return hex(int((sum_result % 1) * 16			)			)[2:]





def 				__UpperCamelCase   (    a__: int ,	a__: int ,	a__: int			)				->			float:




					"""simple docstring"""



					__lowercase												=			0.0
					for sum_index in range(digit_pos_to_extract + precision			):
										__lowercase												=			8 * sum_index + denominator_addend
										if sum_index < digit_pos_to_extract:
															# if the exponential term is an integer and we mod it by the denominator
															# before dividing, only the integer part of the sum will change;
															# the fractional part will not
															__lowercase												=			pow(
															    16 ,	digit_pos_to_extract - 1 - sum_index ,	a__			)
										else:
															__lowercase												=			pow(16 ,	digit_pos_to_extract - 1 - sum_index			)
										total += exponential_term / denominator
					return total


if __name__ == "__main__":
							import doctest

							doctest.testmod()


