


'''simple docstring'''
import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin






class 					lowerCAmelCase_     (    _UpperCAmelCase			,       unittest.TestCase  ):

       '''simple docstring'''





       __UpperCAmelCase				=BertweetTokenizer
       __UpperCAmelCase				=False






       def      UpperCamelCase	(   self      )->			List[Any]:
            super().setUp()

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

            _A				=       os.path.join(self.tmpdirname ,    VOCAB_FILES_NAMES['vocab_file']      )
            _A				=       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(_UpperCamelCase      )      )






       def      UpperCamelCase	(   self ,    **_UpperCamelCase      )->			List[str]:
            kwargs.update(self.special_tokens_map      )
            return BertweetTokenizer.from_pretrained(self.tmpdirname ,    **_UpperCamelCase      )






       def      UpperCamelCase	(   self ,    _UpperCamelCase      )->			Any:
            _A				=       'I am VinAI Research'
            _A				=       'I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
            return input_text, output_text






       def      UpperCamelCase	(   self      )->			str:
            _A				=       BertweetTokenizer(self.vocab_file ,    self.merges_file ,    **self.special_tokens_map      )
            _A				=       'I am VinAI Research'
            _A				=       'I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
            _A				=       tokenizer.tokenize(_UpperCamelCase      )
            self.assertListEqual(_UpperCamelCase ,    _UpperCamelCase      )

            _A				=       tokens + [tokenizer.unk_token]

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









'''simple docstring'''
from itertools import permutations

def 				lowerCamelCase_   (   )				->  Optional[int]:







     """simple docstring"""
     _A				=       list(map(''.join       ,						permutations('0123456789'		)		)		)
     return result[9_9_9_9_9_9]


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





