code: 
  
  
  """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      (lowerCamelCase ,		unittest.TestCase     ):
  							__a				   =					BertweetTokenizer
  							__a				   =					False
  
  
  
  
  							def      __a      (    self:						Any      ):
  										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      __a      (    self:						Dict    ,       **A_:						Any      ):
  										kwargs.update(self.special_tokens_map      )
  										return BertweetTokenizer.from_pretrained(self.tmpdirname    ,       **A_      )
  
  
  
  
  							def      __a      (    self:						Any    ,       A_:						Any      ):
  										__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      __a      (    self:						Tuple      ):
  										__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_      )
  
  
  
  
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  def 			a_   (  lowercase__   :str, lowercase__   :int = 13    ):
  			__lowerCamelCase        =			""""""
  			for c in s:
  						if "A" <= c <= "Z":
  									out += chr(ord("""A"""    ) + (ord(lowercase__    ) - ord("""A"""    ) + n) % 26    )
  						elif "a" <= c <= "z":
  									out += chr(ord("""a"""    ) + (ord(lowercase__    ) - ord("""a"""    ) + n) % 26    )
  						else:
  									out += c
  			return out
  
  
  
  
  
  def 			a_   (  ):
  			__lowerCamelCase        =			input("""Enter message: """    )
  
  			__lowerCamelCase        =			dencrypt(lowercase__, 13    )
  			print("""Encryption:""", lowercase__    )
  
  			__lowerCamelCase        =			dencrypt(lowercase__, 13    )
  			print("""Decryption: """, lowercase__    )
  
  
  if __name__ == "__main__":
  					import doctest
  
  					doctest.testmod()
  					main()
  
  
  
  
  