


'''simple docstring'''
from typing import TYPE_CHECKING

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


lowerCAmelCase__  =     {
    'configuration_flava': [
        'FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'FlavaConfig',
        'FlavaImageCodebookConfig',
        'FlavaImageConfig',
        'FlavaMultimodalConfig',
        'FlavaTextConfig',
    ],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase__  =     ['FlavaFeatureExtractor']
     lowerCAmelCase__  =     ['FlavaImageProcessor']
     lowerCAmelCase__  =     ['FlavaProcessor']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase__  =     [
         'FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST',
         'FlavaForPreTraining',
         'FlavaImageCodebook',
         'FlavaImageModel',
         'FlavaModel',
         'FlavaMultimodalModel',
         'FlavaPreTrainedModel',
         'FlavaTextModel',
     ]

if TYPE_CHECKING:
     from .configuration_flava import (
         FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
         FlavaConfig,
         FlavaImageCodebookConfig,
         FlavaImageConfig,
         FlavaMultimodalConfig,
         FlavaTextConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_flava import FlavaFeatureExtractor
          from .image_processing_flava import FlavaImageProcessor
          from .processing_flava import FlavaProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flava import (
              FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
              FlavaForPreTraining,
              FlavaImageCodebook,
              FlavaImageModel,
              FlavaModel,
              FlavaMultimodalModel,
              FlavaPreTrainedModel,
              FlavaTextModel,
          )

else:
     import sys

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







'''simple docstring'''







from __future__ import annotations

import math
import random






def 					_SCREAMING_SNAKE_CASE		(						snake_case_							,       snake_case_							,       snake_case_	):
	_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							,       snake_case_	)
				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()




