





"""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   (  __snake_case	,						unittest.TestCase		):
     SCREAMING_SNAKE_CASE__ :      Dict       		=			BertweetTokenizer
     SCREAMING_SNAKE_CASE__ :      str       		=			False



     def 						snake_case_			(       self   ):
            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 						snake_case_			(       self					,     **a__   ):
            kwargs.update(self.special_tokens_map   )
            return BertweetTokenizer.from_pretrained(self.tmpdirname					,     **a__   )



     def 						snake_case_			(       self					,     a__   ):
            _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 						snake_case_			(       self   ):
            _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__   )







def 							lowerCAmelCase(	__lowerCamelCase = 10**6						):

					if n <= 0:
										raise ValueError('Please enter an integer greater than 0'						)

					__a							=   list(range(n + 1						)						)
					for number in range(2      ,				n + 1						):
										if phi[number] == number:
															phi[number] -= 1
															for multiple in range(number * 2      ,				n + 1      ,				__lowerCamelCase						):
																				__a							=   (phi[multiple] // number) * (number - 1)

					__a							=   1
					for number in range(1      ,				n + 1						):
										if (answer / phi[answer]) < (number / phi[number]):
															__a							=   number

					return answer


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




