


'''simple docstring'''

from __future__ import annotations

import math
import random

def _SCREAMING_SNAKE_CASE				(A  ,			A  ,			A	)	->	list[int]:






       """simple docstring"""







       lowercase__				      =			d * e - 1
       lowercase__				      =			0
       lowercase__				      =			0
       while p == 0:
              lowercase__				      =			random.randint(2  ,			n - 1	)
              lowercase__				      =			k
              while True:
                     if t % 2 == 0:
                            lowercase__				      =			t // 2
                            lowercase__				      =			(g**t) % n
                            lowercase__				      =			math.gcd(x - 1  ,			A	)
                            if x > 1 and y > 1:
                                   lowercase__				      =			y
                                   lowercase__				      =			n // y
                                   break  # find the correct factors
                     else:
                            break  # t is not divisible by 2, break and choose another g
       return sorted([p, q]	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


lowerCamelCase							:       Tuple  						=     {'configuration_bert_generation': ['BertGenerationConfig']}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Union[str, Any]  						=     ['BertGenerationTokenizer']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:       Dict  						=     [
     'BertGenerationDecoder',
     'BertGenerationEncoder',
     'BertGenerationPreTrainedModel',
     'load_tf_weights_in_bert_generation',
 ]


if TYPE_CHECKING:
 from .configuration_bert_generation import BertGenerationConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_bert_generation import BertGenerationTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bert_generation import (
      BertGenerationDecoder,
      BertGenerationEncoder,
      BertGenerationPreTrainedModel,
      load_tf_weights_in_bert_generation,
  )

else:
 import sys

 lowerCamelCase							:       int  						=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




