



"""simple docstring"""






import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin




class    __snake_case(					A_			,			unittest.TestCase       ):
    _A       = BertweetTokenizer
    _A       = False




    def   A   (   self			):





      '''simple docstring'''



      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   A   (   self    ,							**A_			):





      '''simple docstring'''



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




    def   A   (   self    ,							A_			):





      '''simple docstring'''



      _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   A   (   self			):





      '''simple docstring'''



      _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_			)





def    UpperCAmelCase					(  lowercase__						:					int = 998001	):



			'''simple docstring'''





			for number in range(n - 1				,					9999				,					-1	):
						a__					=  str(lowercase__	)

						# checks whether 'str_number' is a palindrome.
						if str_number == str_number[::-1]:
									a__					=  999

									# if 'number' is a product of two 3-digit numbers
									# then number is the answer otherwise fetch next number.
									while divisor != 99:
												if (number % divisor == 0) and (len(str(number // divisor	)	) == 3.0):
															return number
												divisor -= 1
			raise ValueError("""That number is larger than our acceptable range."""	)


if __name__ == "__main__":
	print(f'''{solution() = }''')

