



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					) ->    List[Any]:
			lowercase__   					=			int(SCREAMING_SNAKE_CASE_					)
			if decimal in (0, 1):  # Exit cases for the recursion
						return str(SCREAMING_SNAKE_CASE_					)
			lowercase__					,    lowercase__   					=			divmod(SCREAMING_SNAKE_CASE_  ,					2					)
			return binary_recursive(SCREAMING_SNAKE_CASE_					) + str(SCREAMING_SNAKE_CASE_					)



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					) ->    Any:
			lowercase__   					=			str(SCREAMING_SNAKE_CASE_					).strip()
			if not number:
						raise ValueError("No input value was provided"					)
			lowercase__   					=			"-" if number.startswith("-"					) else ""
			lowercase__   					=			number.lstrip("-"					)
			if not number.isnumeric():
						raise ValueError("Input value is not an integer"					)
			return f'''{negative}0b{binary_recursive(int(SCREAMING_SNAKE_CASE_					)					)}'''


if __name__ == "__main__":
							from doctest import testmod

							testmod()









from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
							if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							from ...utils.dummy_torch_and_transformers_objects import (
							    VersatileDiffusionDualGuidedPipeline,
							    VersatileDiffusionImageVariationPipeline,
							    VersatileDiffusionPipeline,
							    VersatileDiffusionTextToImagePipeline,
							)
else:
							from .modeling_text_unet import UNetFlatConditionModel
							from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
							from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
							from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
							from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline




