

import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin







class  UpperCamelCase_      (	_snake_case		,  unittest.TestCase      ):


  """simple docstring"""
  SCREAMING_SNAKE_CASE__					:			Dict					    =   BertweetTokenizer
  SCREAMING_SNAKE_CASE__					:			Optional[int]					    =   False



  def   _UpperCamelCase     (						self     :					str						)       ->			Dict:
      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(A_  ,	range(len(A_						)						)						)						)
      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(A_						)						)



  def   _UpperCamelCase     (						self     :					Optional[Any]  ,	**A_     :					int						)       ->			str:
      kwargs.update(self.special_tokens_map						)
      return BertweetTokenizer.from_pretrained(self.tmpdirname  ,	**A_						)



  def   _UpperCamelCase     (						self     :					Union[str, Any]  ,	A_     :					int						)       ->			Any:
      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   _UpperCamelCase     (						self     :					Any						)       ->			Optional[int]:
      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(A_						)
      self.assertListEqual(A_  ,	A_						)

      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(A_						)  ,	A_						)





A__										=      10**8





def 				__a							(       __A						):
    if n % 10 == 0:
        return False
    SCREAMING_SNAKE_CASE__         =    str(__A						)
    return s == s[::-1]





def 				__a							(       ):
    SCREAMING_SNAKE_CASE__         =    set()
    SCREAMING_SNAKE_CASE__         =    1
    SCREAMING_SNAKE_CASE__         =    5
    while sum_squares < LIMIT:
        SCREAMING_SNAKE_CASE__         =    first_square + 1
        while sum_squares < LIMIT:
            if is_palindrome(__A						):
                answer.add(__A						)
            last_square += 1
            sum_squares += last_square**2
        first_square += 1
        SCREAMING_SNAKE_CASE__         =    first_square**2 + (first_square + 1) ** 2

    return sum(__A						)


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


