code: 
  '''simple docstring'''
  from __future__ import annotations
  
  
  
  
  def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )     ->       tuple[float, float]:
  
  
    '''simple docstring'''
  
  
    assert (
        c % greatest_common_divisor(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ ) == 0
    )  # greatest_common_divisor(a,b) function implemented below
    (snake_case)     :					Tuple     =	extended_gcd(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )  # extended_gcd(a,b) function implemented below
    snake_case     :					Tuple     =	c / d
    return (r * x, r * y)
  
  
  
  
  def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ = 2 )     ->       None:
  
  
    '''simple docstring'''
  
  
    (snake_case)     :					List[Any]     =	diophantine(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )  # Initial value
    snake_case     :					int     =	greatest_common_divisor(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )
    snake_case     :					Optional[int]     =	a // d
    snake_case     :					Optional[Any]     =	b // d
  
    for i in range(SCREAMING_SNAKE_CASE__ ):
      snake_case     :					int     =	xa + i * q
      snake_case     :					int     =	ya - i * p
      print(SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )
  
  
  
  
  def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )     ->       int:
  
  
    '''simple docstring'''
  
  
    if a < b:
      snake_case     :					Dict     =	b, a
  
    while a % b != 0:
      snake_case     :					Optional[Any]     =	b, a % b
  
    return b
  
  
  
  
  def       _UpperCamelCase	(					SCREAMING_SNAKE_CASE__   ,					SCREAMING_SNAKE_CASE__ )     ->       tuple[int, int, int]:
  
  
    '''simple docstring'''
  
  
    assert a >= 0 and b >= 0
  
    if b == 0:
      snake_case     :					Any     =	a, 1, 0
    else:
      (snake_case)     :					Optional[Any]     =	extended_gcd(SCREAMING_SNAKE_CASE__   ,					a % b )
      snake_case     :					List[Any]     =	q
      snake_case     :					str     =	p - q * (a // b)
  
    assert a % d == 0 and b % d == 0
    assert d == a * x + b * y
  
    return (d, x, y)
  
  
  if __name__ == "__main__":
        from doctest import testmod
  
        testmod(name="diophantine", verbose=True)
        testmod(name="diophantine_all_soln", verbose=True)
        testmod(name="extended_gcd", verbose=True)
        testmod(name="greatest_common_divisor", verbose=True)
  
  
  
style_context: 
  '''simple docstring'''
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  lowercase__						=			{
      "configuration_flava": [
          "FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "FlavaConfig",
          "FlavaImageCodebookConfig",
          "FlavaImageConfig",
          "FlavaMultimodalConfig",
          "FlavaTextConfig",
      ],
  }
  
  try:
  						if not is_vision_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						lowercase__						=			["FlavaFeatureExtractor"]
  						lowercase__						=			["FlavaImageProcessor"]
  						lowercase__						=			["FlavaProcessor"]
  
  try:
  						if not is_torch_available():
  												raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  						pass
  else:
  						lowercase__						=			[
  						    "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
  
  						lowercase__						=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  