

import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class 		a_	(							lowerCamelCase_			,      unittest.TestCase					):



      """simple docstring"""







      __UpperCAmelCase      		=				BertweetTokenizer
      __UpperCAmelCase      		=				False
      def 	_lowerCAmelCase					(				self					:							Union[str, Any]    ):
           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           SCREAMING_SNAKE_CASE										=['I', 'm', 'V@@', 'R@@', 'r', 'e@@']
           SCREAMING_SNAKE_CASE										=dict(zip(snake_case      ,range(len(snake_case    )    )    )    )
           SCREAMING_SNAKE_CASE										=['#version: 0.2', 'a m</w>']
           SCREAMING_SNAKE_CASE										={'unk_token': '<unk>'}

           SCREAMING_SNAKE_CASE										=os.path.join(self.tmpdirname      ,VOCAB_FILES_NAMES['vocab_file']    )
           SCREAMING_SNAKE_CASE										=os.path.join(self.tmpdirname      ,VOCAB_FILES_NAMES['merges_file']    )
           with open(self.vocab_file      ,'w'      ,encoding='utf-8'    ) as fp:
                for token in vocab_tokens:
                     fp.write(f'{token} {vocab_tokens[token]}\n'    )
           with open(self.merges_file      ,'w'      ,encoding='utf-8'    ) as fp:
                fp.write('\n'.join(snake_case    )    )
      def 	_lowerCAmelCase					(				self					:							str      ,**snake_case					:							int    ):
           kwargs.update(self.special_tokens_map    )
           return BertweetTokenizer.from_pretrained(self.tmpdirname      ,**snake_case    )
      def 	_lowerCAmelCase					(				self					:							List[str]      ,snake_case					:							int    ):
           SCREAMING_SNAKE_CASE										='I am VinAI Research'
           SCREAMING_SNAKE_CASE										='I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
           return input_text, output_text


      def 	_lowerCAmelCase					(				self					:							Any    ):
           SCREAMING_SNAKE_CASE										=BertweetTokenizer(self.vocab_file      ,self.merges_file      ,**self.special_tokens_map    )
           SCREAMING_SNAKE_CASE										='I am VinAI Research'
           SCREAMING_SNAKE_CASE										='I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
           SCREAMING_SNAKE_CASE										=tokenizer.tokenize(snake_case    )
           self.assertListEqual(snake_case      ,snake_case    )

           SCREAMING_SNAKE_CASE										=tokens + [tokenizer.unk_token]

           SCREAMING_SNAKE_CASE										=[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case    )      ,snake_case    )




import decimal







def       snake_case__    (       ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE										=0
     SCREAMING_SNAKE_CASE										=decimal.Context(prec=105      )
     for i in range(2,   100      ):
          SCREAMING_SNAKE_CASE										=decimal.Decimal(lowerCAmelCase_      )
          SCREAMING_SNAKE_CASE										=number.sqrt(lowerCAmelCase_      )
          if len(str(lowerCAmelCase_      )      ) > 1:
               answer += int(str(lowerCAmelCase_      )[0]      )
               SCREAMING_SNAKE_CASE										=str(lowerCAmelCase_      )[2:101]
               answer += sum(int(lowerCAmelCase_      ) for x in sqrt_number_str      )
     return answer


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(f'{solution() = }')

