





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin

class 		UpperCamelCase__ (      lowerCAmelCase_							,      unittest.TestCase   ):



     '''simple docstring'''

     __snake_case    :	Optional[Any]			=			BioGptTokenizer
     __snake_case    :	List[str]			=			False






     def 				SCREAMING_SNAKE_CASE__  (							self						:    str       )     ->		List[str]:




           '''simple docstring'''


           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           SCREAMING_SNAKE_CASE		=						[
               """l""",
               """o""",
               """w""",
               """e""",
               """r""",
               """s""",
               """t""",
               """i""",
               """d""",
               """n""",
               """w</w>""",
               """r</w>""",
               """t</w>""",
               """lo""",
               """low""",
               """er</w>""",
               """low</w>""",
               """lowest</w>""",
               """newer</w>""",
               """wider</w>""",
               """<unk>""",
           ]
           SCREAMING_SNAKE_CASE		=						dict(zip(lowerCamelCase__						,range(len(lowerCamelCase__       )       )       )       )
           SCREAMING_SNAKE_CASE		=						["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

           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"""       ) as fp:
                 fp.write(json.dumps(lowerCamelCase__       )       )
           with open(self.merges_file						,"""w"""       ) as fp:
                 fp.write("""\n""".join(lowerCamelCase__       )       )






     def 				SCREAMING_SNAKE_CASE__  (							self						:    int						,lowerCamelCase__						:    Tuple       )     ->		Tuple:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						"""lower newer"""
           SCREAMING_SNAKE_CASE		=						"""lower newer"""
           return input_text, output_text






     def 				SCREAMING_SNAKE_CASE__  (							self						:    Any       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BioGptTokenizer(self.vocab_file						,self.merges_file       )

           SCREAMING_SNAKE_CASE		=						"""lower"""
           SCREAMING_SNAKE_CASE		=						["""low""", """er</w>"""]
           SCREAMING_SNAKE_CASE		=						tokenizer.tokenize(lowerCamelCase__       )
           self.assertListEqual(lowerCamelCase__						,lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						tokens + ["""<unk>"""]
           SCREAMING_SNAKE_CASE		=						[14, 15, 20]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase__       )						,lowerCamelCase__       )






     @slow
     def 				SCREAMING_SNAKE_CASE__  (							self						:    Any       )     ->		List[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						BioGptTokenizer.from_pretrained("""microsoft/biogpt"""       )

           SCREAMING_SNAKE_CASE		=						tokenizer.encode("""sequence builders"""						,add_special_tokens=lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						tokenizer.encode("""multi-sequence build"""						,add_special_tokens=lowerCamelCase__       )

           SCREAMING_SNAKE_CASE		=						tokenizer.build_inputs_with_special_tokens(lowerCamelCase__       )
           SCREAMING_SNAKE_CASE		=						tokenizer.build_inputs_with_special_tokens(lowerCamelCase__						,lowerCamelCase__       )

           self.assertTrue(encoded_sentence == [2] + text       )
           self.assertTrue(encoded_pair == [2] + text + [2] + text_a       )









import random

class 		UpperCamelCase__ :



     '''simple docstring'''

     @staticmethod
     def 				SCREAMING_SNAKE_CASE__  (							lowerCamelCase__						:    str       )     ->		tuple[list[int], list[int]]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[ord(lowerCamelCase__       ) for i in text]
           SCREAMING_SNAKE_CASE		=						[]
           SCREAMING_SNAKE_CASE		=						[]
           for i in plain:
                 SCREAMING_SNAKE_CASE		=						random.randint(1						,300       )
                 SCREAMING_SNAKE_CASE		=						(i + k) * k
                 cipher.append(lowerCamelCase__       )
                 key.append(lowerCamelCase__       )
           return cipher, key






     @staticmethod
     def 				SCREAMING_SNAKE_CASE__  (							lowerCamelCase__						:    list[int]						,lowerCamelCase__						:    list[int]       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[]
           for i in range(len(lowerCamelCase__       )       ):
                 SCREAMING_SNAKE_CASE		=						int((cipher[i] - (key[i]) ** 2) / key[i]       )
                 plain.append(chr(lowerCamelCase__       )       )
           return "".join(lowerCamelCase__       )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE_   ,						SCREAMING_SNAKE_CASE_						   =       Onepad().encrypt("""Hello""")
      print(c, k)
      print(Onepad().decrypt(c, k))


