



from __future__ import annotations

from bisect import bisect_left
from functools import total_ordering
from heapq import merge



@total_ordering
class   UpperCAmelCase_    (       a):







							def __lt__(   self,			__a):

														'''simple docstring'''

														return self[-1] < other[-1]







							def __eq__(   self,			__a):

														'''simple docstring'''

														return self[-1] == other[-1]






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							list[Stack]    =    []
							# sort into stacks
							for element in collection:
														_lowerCAmelCase     :							Optional[Any]    =    Stack([element]  )
														_lowerCAmelCase     :							Union[str, Any]    =    bisect_left(_lowerCamelCase				, _lowerCamelCase  )
														if i != len(_lowerCamelCase  ):
																					stacks[i].append(_lowerCamelCase  )
														else:
																					stacks.append(_lowerCamelCase  )

    # use a heap-based merge to merge stack efficiently
							_lowerCAmelCase     :							Dict    =    merge(*(reversed(_lowerCamelCase  ) for stack in stacks)  )
							return collection


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





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
