



"""simple docstring"""


from __future__ import annotations

import math
import random

def 					_lowerCAmelCase (  lowercase_						,      lowercase_						,      lowercase_		):
						UpperCAmelCase			 =					d * e - 1
						UpperCAmelCase			 =					0
						UpperCAmelCase			 =					0
						while p == 0:
												UpperCAmelCase			 =					random.randint(2						,      n - 1		)
												UpperCAmelCase			 =					k
												while True:
																		if t % 2 == 0:
																								UpperCAmelCase			 =					t // 2
																								UpperCAmelCase			 =					(g**t) % n
																								UpperCAmelCase			 =					math.gcd(x - 1						,      lowercase_		)
																								if x > 1 and y > 1:
																														UpperCAmelCase			 =					y
																														UpperCAmelCase			 =					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()






from typing import TYPE_CHECKING

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


UpperCamelCase    				=		{'''configuration_vit_hybrid''': ['''VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTHybridConfig''']}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    				=		[
          '''VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''ViTHybridForImageClassification''',
          '''ViTHybridModel''',
          '''ViTHybridPreTrainedModel''',
      ]

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase    				=		['''ViTHybridImageProcessor''']


if TYPE_CHECKING:
      from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_vit_hybrid import (
                VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
                ViTHybridForImageClassification,
                ViTHybridModel,
                ViTHybridPreTrainedModel,
            )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
      import sys

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



