
from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest

@require_tokenizers
class 		lowercase_							(							__SCREAMING_SNAKE_CASE					):
 A__    :					Optional[Any]    =     DPRContextEncoderTokenizer
 A__    :					Optional[Any]    =     DPRContextEncoderTokenizerFast
 A__    :					Tuple    =     True



@require_tokenizers
class 		lowercase_							(							__SCREAMING_SNAKE_CASE					):
 A__    :					Optional[int]    =     DPRQuestionEncoderTokenizer
 A__    :					Tuple    =     DPRQuestionEncoderTokenizerFast
 A__    :					Optional[int]    =     True



@require_tokenizers
class 		lowercase_							(							__SCREAMING_SNAKE_CASE					):
 A__    :					List[Any]    =     DPRReaderTokenizer
 A__    :					List[str]    =     DPRReaderTokenizerFast
 A__    :					Dict    =     True

 @slow
 def lowerCamelCase_					(   self  ):




        """simple docstring"""


        UpperCamelCase_											=							self.tokenizer_class.from_pretrained("""bert-base-uncased"""  )

        UpperCamelCase_											=							tokenizer.encode("""question sequence"""  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							tokenizer.encode("""title sequence"""  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							tokenizer.encode("""text sequence """ * 4  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							[[1_0_1] + text_a + [1_0_2] + text_a + [1_0_2] + text_a]
        UpperCamelCase_											=							BatchEncoding({"""input_ids""": input_ids}  )

        UpperCamelCase_											=							[[0] * len(input_ids[0]  )]
        UpperCamelCase_											=							[[0] * len(input_ids[0]  )]
        UpperCamelCase_											=							[0]
        UpperCamelCase_											=							DPRReaderOutput(__UpperCamelCase  ,						__UpperCamelCase  ,						__UpperCamelCase  )

        UpperCamelCase_							,					UpperCamelCase_											=							8, 9
        UpperCamelCase_											=							1_0
        UpperCamelCase_											=							1_0
        UpperCamelCase_											=							tokenizer.decode_best_spans(__UpperCamelCase  ,						__UpperCamelCase  )
        self.assertEqual(predicted_spans[0].start_index  ,						__UpperCamelCase  )
        self.assertEqual(predicted_spans[0].end_index  ,						__UpperCamelCase  )
        self.assertEqual(predicted_spans[0].doc_id  ,						0  )

 @slow
 def lowerCamelCase_					(   self  ):




        """simple docstring"""


        UpperCamelCase_											=							self.tokenizer_class.from_pretrained("""bert-base-uncased"""  )

        UpperCamelCase_											=							tokenizer.encode("""question sequence"""  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							tokenizer.encode("""title sequence"""  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							tokenizer.encode("""text sequence"""  ,						add_special_tokens=__UpperCamelCase  )
        UpperCamelCase_											=							[1_0_1] + text_a + [1_0_2] + text_a + [1_0_2] + text_a
        UpperCamelCase_											=							tokenizer(questions=["""question sequence"""]  ,						titles=["""title sequence"""]  ,						texts=["""text sequence"""]  )
        self.assertIn("""input_ids"""  ,						__UpperCamelCase  )
        self.assertIn("""attention_mask"""  ,						__UpperCamelCase  )
        self.assertListEqual(encoded_input["""input_ids"""][0]  ,						__UpperCamelCase  )





_A							=       [chr(i) for i in range(32, 126)]
_A							=       list(range(len(alphabets)))
_A							=       list(range(len(alphabets)))
_A							=       list(range(len(alphabets)))
_A							=       list(reversed(range(len(alphabets))))
_A							=       []
_A							=       _A							=       _A							=       0




def 					lowerCamelCase__					(    )		->						List[str]:
       global gear_one_pos
       global gear_two_pos
       global gear_three_pos
       UpperCamelCase_											=							gear_one[0]
       gear_one.append(a__  )
       del gear_one[0]
       gear_one_pos += 1
       if gear_one_pos % int(len(a__  )  ) == 0:
              UpperCamelCase_											=							gear_two[0]
              gear_two.append(a__  )
              del gear_two[0]
              gear_two_pos += 1
              if gear_two_pos % int(len(a__  )  ) == 0:
                     UpperCamelCase_											=							gear_three[0]
                     gear_three.append(a__  )
                     del gear_three[0]
                     gear_three_pos += 1




def 					lowerCamelCase__					(    a__	:	Optional[int]  )		->						Any:
       UpperCamelCase_											=							alphabets.index(a__  )
       UpperCamelCase_											=							gear_one[target]
       UpperCamelCase_											=							gear_two[target]
       UpperCamelCase_											=							gear_three[target]
       UpperCamelCase_											=							reflector[target]
       UpperCamelCase_											=							gear_three.index(a__  )
       UpperCamelCase_											=							gear_two.index(a__  )
       UpperCamelCase_											=							gear_one.index(a__  )
       code.append(alphabets[target]  )
       rotator()


if __name__ == "__main__":
      _A							=       list(input('''Type your message:\n'''))
      while True:
            try:
                  _A							=       int(input('''Please set token:(must be only digits)\n'''))
                  break
            except Exception as error:
                  print(error)
      for _ in range(token):
            rotator()
      for j in decode:
            engine(j)
      print('''\n''' + ''''''.join(code))
      print(
          F'''\nYour Token is {token} please write it down.\nIf you want to decode '''
          '''this message again you should input same digits as token!'''
      )



