





import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 					__magic_name__  (							lowerCamelCase__    ,				unittest.TestCase							):





     """simple docstring"""



     __UpperCamelCase					    =     MPNetTokenizer
     __UpperCamelCase					    =     MPNetTokenizerFast
     __UpperCamelCase					    =     True
     __UpperCamelCase					    =     True



     def 						SCREAMING_SNAKE_CASE		(							self       :List[str]  ):





        '''simple docstring'''




        super().setUp()

        A_					:				int          =			[
            "[UNK]",
            "[CLS]",
            "[SEP]",
            "[PAD]",
            "[MASK]",
            "want",
            "##want",
            "##ed",
            "wa",
            "un",
            "runn",
            "##ing",
            ",",
            "low",
            "lowest",
        ]
        A_					:				List[str]          =			os.path.join(self.tmpdirname			,      VOCAB_FILES_NAMES["vocab_file"]  )
        with open(self.vocab_file			,      "w"			,      encoding="utf-8"  ) as vocab_writer:
           vocab_writer.write("".join([x + "\n" for x in vocab_tokens]  )  )



     def 						SCREAMING_SNAKE_CASE		(							self       :List[Any]			,      snake_case       :Union[str, Any]  ):





        '''simple docstring'''




        A_					:				str          =			"UNwant\u00E9d,running"
        A_					:				Union[str, Any]          =			"unwanted, running"
        return input_text, output_text



     def 						SCREAMING_SNAKE_CASE		(							self       :List[str]  ):





        '''simple docstring'''




        A_					:				Union[str, Any]          =			self.tokenizer_class(self.vocab_file  )

        A_					:				Union[str, Any]          =			tokenizer.tokenize("UNwant\u00E9d,running"  )
        self.assertListEqual(snake_case			,      ["un", "##want", "##ed", ",", "runn", "##ing"]  )
        self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case  )			,      [9, 6, 7, 12, 10, 11]  )





     @slow
     def 						SCREAMING_SNAKE_CASE		(							self       :List[str]  ):





        '''simple docstring'''




        A_					:				Optional[int]          =			self.tokenizer_class.from_pretrained("microsoft/mpnet-base"  )

        A_					:				Optional[int]          =			tokenizer.encode("sequence builders"			,      add_special_tokens=snake_case  )
        A_					:				Union[str, Any]          =			tokenizer.encode("multi-sequence build"			,      add_special_tokens=snake_case  )

        A_					:				Union[str, Any]          =			tokenizer.build_inputs_with_special_tokens(snake_case  )
        A_					:				Dict          =			tokenizer.build_inputs_with_special_tokens(snake_case			,      snake_case  )

        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]






def      __snake_case						(					_lowerCAmelCase : int				,				_lowerCAmelCase : int = 1000	) ->						str:
   if (not isinstance(_lowerCAmelCase				,				_lowerCAmelCase	)) or (digit_position <= 0):
      raise ValueError("Digit position must be a positive integer"	)
   elif (not isinstance(_lowerCAmelCase				,				_lowerCAmelCase	)) 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
   A_					:				List[str]          =			(
       4 * _subsum(_lowerCAmelCase				,				1				,				_lowerCAmelCase	)
       - 2 * _subsum(_lowerCAmelCase				,				4				,				_lowerCAmelCase	)
       - _subsum(_lowerCAmelCase				,				5				,				_lowerCAmelCase	)
       - _subsum(_lowerCAmelCase				,				6				,				_lowerCAmelCase	)
   )

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

def      __snake_case						(					_lowerCAmelCase : int				,				_lowerCAmelCase : int				,				_lowerCAmelCase : int	) ->						float:
   A_					:				int          =			0.0
   for sum_index in range(digit_pos_to_extract + precision	):
      A_					:				Optional[int]          =			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
         A_					:				Optional[Any]          =			pow(
             16				,				digit_pos_to_extract - 1 - sum_index				,				_lowerCAmelCase	)
      else:
         A_					:				Tuple          =			pow(16				,				digit_pos_to_extract - 1 - sum_index	)
      total += exponential_term / denominator
   return total


if __name__ == "__main__":
 import doctest

 doctest.testmod()
