






"""simple docstring"""
from __future__ import annotations






def        lowerCamelCase_  (						_lowerCamelCase				):


 for r in range(1			,   a_				):
  lowerCamelCase__     :			Tuple     				=						[]
  for x in range(n - 1				):
   lowerCamelCase__     :			List[str]     				=						pow(a_			,   a_			,   a_				)
   if val in li:
    break
   li.append(a_				)
  else:
   return r
 return None


if __name__ == "__main__":
      A_			: str				=			int(input("Enter a prime number q: "))
      A_			: Optional[Any]				=			find_primitive(q)
      if a is None:
            print(f"Cannot find the primitive for the value: {a!r}")
      else:
            A_			: Optional[int]				=			int(input("Enter private key of A: "))
            A_			: Optional[Any]				=			pow(a, a_private, q)
            A_			: int				=			int(input("Enter private key of B: "))
            A_			: Optional[int]				=			pow(a, b_private, q)

            A_			: Optional[int]				=			pow(b_public, a_private, q)
            A_			: Union[str, Any]				=			pow(a_public, b_private, q)

            print("The key value generated by A is: ", a_secret)
            print("The key value generated by B is: ", b_secret)



"""simple docstring"""

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   (				__UpperCAmelCase		):
	lowercase_        =	DPRContextEncoderTokenizer
	lowercase_        =	DPRContextEncoderTokenizerFast
	lowercase_        =	True






@require_tokenizers
class        _lowercase   (				__UpperCAmelCase		):
	lowercase_        =	DPRQuestionEncoderTokenizer
	lowercase_        =	DPRQuestionEncoderTokenizerFast
	lowercase_        =	True






@require_tokenizers
class        _lowercase   (				__UpperCAmelCase		):
	lowercase_        =	DPRReaderTokenizer
	lowercase_        =	DPRReaderTokenizerFast
	lowercase_        =	True




	@slow
	def 			_UpperCamelCase    ( self					)		->							Any:
			lowerCamelCase     :			str		=    self.tokenizer_class.from_pretrained('bert-base-uncased'					)

			lowerCamelCase     :			int		=    tokenizer.encode('question sequence'		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			List[Any]		=    tokenizer.encode('title sequence'		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			Optional[int]		=    tokenizer.encode('text sequence ' * 4		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			Union[str, Any]		=    [[101] + text_a + [102] + text_a + [102] + text_a]
			lowerCamelCase     :			List[str]		=    BatchEncoding({'input_ids': input_ids}					)

			lowerCamelCase     :			Optional[int]		=    [[0] * len(input_ids[0]					)]
			lowerCamelCase     :			str		=    [[0] * len(input_ids[0]					)]
			lowerCamelCase     :			List[Any]		=    [0]
			lowerCamelCase     :			Tuple		=    DPRReaderOutput(UpperCAmelCase_		, UpperCAmelCase_		, UpperCAmelCase_					)

			lowerCamelCase	,    lowerCamelCase     :			Optional[int]		=    8, 9
			lowerCamelCase     :			Optional[int]		=    10
			lowerCamelCase     :			int		=    10
			lowerCamelCase     :			List[Any]		=    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 			_UpperCamelCase    ( self					)		->							List[Any]:
			lowerCamelCase     :			Union[str, Any]		=    self.tokenizer_class.from_pretrained('bert-base-uncased'					)

			lowerCamelCase     :			List[str]		=    tokenizer.encode('question sequence'		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			List[str]		=    tokenizer.encode('title sequence'		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			List[Any]		=    tokenizer.encode('text sequence'		, add_special_tokens=UpperCAmelCase_					)
			lowerCamelCase     :			List[Any]		=    [101] + text_a + [102] + text_a + [102] + text_a
			lowerCamelCase     :			Optional[Any]		=    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_					)






