'''simple docstring'''




import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin





class 					a__   (     UpperCAmelCase__							,     unittest.TestCase				):
     lowerCamelCase						:  List[Any]							=BertweetTokenizer
     lowerCamelCase						:  int							=False






     def      SCREAMING_SNAKE_CASE__     (				self	:	List[Any]					):





         """simple docstring"""



         super().setUp()

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

         __lowerCamelCase						=						os.path.join(self.tmpdirname						,       VOCAB_FILES_NAMES['''vocab_file''']					)
         __lowerCamelCase						=						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(a					)					)






     def      SCREAMING_SNAKE_CASE__     (				self	:	Dict						,       **a	:	int					):





         """simple docstring"""



         kwargs.update(self.special_tokens_map					)
         return BertweetTokenizer.from_pretrained(self.tmpdirname						,       **a					)






     def      SCREAMING_SNAKE_CASE__     (				self	:	Union[str, Any]						,       a	:	Union[str, Any]					):





         """simple docstring"""



         __lowerCamelCase						=						'''I am VinAI Research'''
         __lowerCamelCase						=						'''I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
         return input_text, output_text






     def      SCREAMING_SNAKE_CASE__     (				self	:	Tuple					):





         """simple docstring"""



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

         __lowerCamelCase						=						tokens + [tokenizer.unk_token]

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

'''simple docstring'''




__UpperCAmelCase  							=1_0**8






def __lowerCAmelCase				(							UpperCamelCase__       )			->					bool:
    if n % 10 == 0:
        return False
    __lowerCamelCase						=						str(UpperCamelCase__       )
    return s == s[::-1]






def __lowerCAmelCase				(							)			->					int:
    __lowerCamelCase						=						set()
    __lowerCamelCase						=						1
    __lowerCamelCase						=						5
    while sum_squares < LIMIT:
        __lowerCamelCase						=						first_square + 1
        while sum_squares < LIMIT:
            if is_palindrome(UpperCamelCase__       ):
                answer.add(UpperCamelCase__       )
            last_square += 1
            sum_squares += last_square**2
        first_square += 1
        __lowerCamelCase						=						first_square**2 + (first_square + 1) ** 2

    return sum(UpperCamelCase__       )


if __name__ == "__main__":
  print(solution())
