'''simple docstring'''




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




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






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





         """simple docstring"""



         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         __lowerCamelCase		=  ['''T@@''', '''i''', '''I''', '''R@@''', '''r''', '''e@@''']
         __lowerCamelCase		=  dict(zip(a  ,				range(len(a    )    )    )    )
         __lowerCamelCase		=  ['''#version: 0.2''', '''l à</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		:		int  ,				**a		:		List[str]    ):





         """simple docstring"""



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






     def    SCREAMING_SNAKE_CASE__   ( self		:		str  ,				a		:		Tuple    ):





         """simple docstring"""



         __lowerCamelCase		=  '''Tôi là VinAI Research'''
         __lowerCamelCase		=  '''T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'''
         return input_text, output_text






     def    SCREAMING_SNAKE_CASE__   ( self		:		int    ):





         """simple docstring"""



         __lowerCamelCase		=  PhobertTokenizer(self.vocab_file  ,				self.merges_file  ,				**self.special_tokens_map    )
         __lowerCamelCase		=  '''Tôi là VinAI Research'''
         __lowerCamelCase		=  '''T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'''.split()
         __lowerCamelCase		=  tokenizer.tokenize(a    )
         print(a    )
         self.assertListEqual(a  ,				a    )

         __lowerCamelCase		=  tokens + [tokenizer.unk_token]

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





'''simple docstring'''

import math



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      bool:
		_a     :      Optional[int]        =							math.loga(math.sqrt(4 * positive_integer + 1  ) / 2 + 1 / 2  )

		return exponent == int(lowerCAmelCase_  )



def      __lowerCamelCase     (      lowerCAmelCase_ = 1 / 12345  )			->      int:
		_a     :      int        =							0
		_a     :      Optional[Any]        =							0

		_a     :      int        =							3
		while True:
				_a     :      Tuple        =							(integer**2 - 1) / 4
				# if candidate is an integer, then there is a partition for k
				if partition_candidate == int(lowerCAmelCase_  ):
						_a     :      Union[str, Any]        =							int(lowerCAmelCase_  )
						total_partitions += 1
						if check_partition_perfect(lowerCAmelCase_  ):
								perfect_partitions += 1
				if perfect_partitions > 0:
						if perfect_partitions / total_partitions < max_proportion:
								return int(lowerCAmelCase_  )
				integer += 1


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




