






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


try:
							if not (is_transformers_available() and is_torch_available()):
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							from ...utils.dummy_torch_and_transformers_objects import ShapEPipeline
else:
							from .camera import create_pan_cameras
							from .pipeline_shap_e import ShapEPipeline
							from .pipeline_shap_e_img2img import ShapEImgaImgPipeline
							from .renderer import (
							    BoundingBoxVolume,
							    ImportanceRaySampler,
							    MLPNeRFModelOutput,
							    MLPNeRSTFModel,
							    ShapEParamsProjModel,
							    ShapERenderer,
							    StratifiedRaySampler,
							    VoidNeRFModel,
							)





'''simple docstring'''






def 		UpperCamelCase__      (		__SCREAMING_SNAKE_CASE		)    ->   str:
      snake_case__      ,							snake_case__       :   Optional[int]	      =    [], []
      while len(__SCREAMING_SNAKE_CASE		) > 1:
            snake_case__      ,							snake_case__       :   Tuple	      =    min(__SCREAMING_SNAKE_CASE		), max(__SCREAMING_SNAKE_CASE		)
            start.append(__SCREAMING_SNAKE_CASE		)
            end.append(__SCREAMING_SNAKE_CASE		)
            collection.remove(__SCREAMING_SNAKE_CASE		)
            collection.remove(__SCREAMING_SNAKE_CASE		)
      end.reverse()
      return start + collection + end


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