from __future__ import annotations


def SCREAMING_SNAKE_CASE			(       lowercase_:		int			):
       for r in range(1						,  lowercase_			):
              _UpperCamelCase       :    List[str]					  =					[]
              for x in range(n - 1			):
                     _UpperCamelCase       :    int					  =					pow(lowercase_						,  lowercase_						,  lowercase_			)
                     if val in li:
                            break
                     li.append(lowercase_			)
              else:
                     return r
       return None


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

  UpperCAmelCase     						=			pow(b_public, a_private, q)
  UpperCAmelCase     						=			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)




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


UpperCAmelCase     						=			{
    '''configuration_speech_to_text_2''': ['''SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Speech2Text2Config'''],
    '''processing_speech_to_text_2''': ['''Speech2Text2Processor'''],
    '''tokenization_speech_to_text_2''': ['''Speech2Text2Tokenizer'''],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase     						=			[
     '''SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Speech2Text2ForCausalLM''',
     '''Speech2Text2PreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
 from .processing_speech_to_text_a import SpeechaTextaProcessor
 from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_speech_to_text_a import (
      SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
      SpeechaTextaForCausalLM,
      SpeechaTextaPreTrainedModel,
  )

else:
 import sys

 UpperCAmelCase     						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



