


"""simple docstring"""



from __future__ import annotations
def     UpperCAmelCase    (					_lowercase   :      int  )	->   int | None:


	"""simple docstring"""




	for r in range(1 ,      _lowercase  ):
		lowerCAmelCase_			       = []
		for x in range(n - 1  ):
			lowerCAmelCase_			       = pow(_lowercase ,      _lowercase ,      _lowercase  )
			if val in li:
				break
			li.append(_lowercase  )
		else:
			return r
	return None


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

				lowercase_							 =       pow(b_public, a_private, q)
				lowercase_							 =       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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_							 =       {
    'configuration_prophetnet': ['PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ProphetNetConfig'],
    'tokenization_prophetnet': ['ProphetNetTokenizer'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							 =       [
		    'PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ProphetNetDecoder',
		    'ProphetNetEncoder',
		    'ProphetNetForCausalLM',
		    'ProphetNetForConditionalGeneration',
		    'ProphetNetModel',
		    'ProphetNetPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
		from .tokenization_prophetnet import ProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_prophetnet import (
				    PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ProphetNetDecoder,
				    ProphetNetEncoder,
				    ProphetNetForCausalLM,
				    ProphetNetForConditionalGeneration,
				    ProphetNetModel,
				    ProphetNetPreTrainedModel,
				)

else:
		import sys

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