




"""simple docstring"""






def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     Optional[Any]       =       len(lowercase__						)
				while cur > 1:
								# Find the maximum number in arr
								_lowerCamelCase	:     Optional[int]       =       arr.index(max(arr[0:cur]						)						)
								# Reverse from 0 to mi
								_lowerCamelCase	:     Dict       =       arr[mi::-1] + arr[mi + 1 : len(lowercase__						)]
								# Reverse whole list
								_lowerCamelCase	:     Tuple       =       arr[cur - 1 :: -1] + arr[cur : len(lowercase__						)]
								cur -= 1
				return arr


if __name__ == "__main__":
			lowercase__			=		input("""Enter numbers separated by a comma:\n""").strip()
			lowercase__			=		[int(item) for item in user_input.split(""",""")]
			print(pancake_sort(unsorted))





"""simple docstring"""






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