




'''simple docstring'''





from __future__ import annotations

def       SCREAMING_SNAKE_CASE							(     __UpperCamelCase)    ->  Optional[Any]:
     for r in range(1	,      __UpperCamelCase):
          a											=   []
          for x in range(n - 1):
               a											=   pow(__UpperCamelCase	,      __UpperCamelCase	,      __UpperCamelCase)
               if val in li:
                    break
               li.append(__UpperCamelCase)
          else:
               return r
     return None


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

      lowercase__   :    Optional[Any] 					=      pow(b_public, a_private, q)
      lowercase__   :    Optional[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)







from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available




@dataclass
class     a__ (      UpperCamelCase__   ):
     a	:    Union[List[PIL.Image.Image], np.ndarray]


if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
   from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
   from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline

