"""simple docstring"""
def    lowerCAmelCase__    (			_UpperCamelCase       :				Any					)					->				list:





						"""simple docstring"""






						if any(not isinstance(lowerCamelCase_ ,			lowerCamelCase_					) or x < 0 for x in sequence					):
												raise TypeError('Sequence must be list of non-negative integers'					)
						for _ in range(len(lowerCamelCase_					)					):
												for i, (rod_upper, rod_lower) in enumerate(zip(lowerCamelCase_ ,			sequence[1:]					)					):
																		if rod_upper > rod_lower:
																								sequence[i] -= rod_upper - rod_lower
																								sequence[i + 1] += rod_upper - rod_lower
						return sequence


if __name__ == "__main__":
					assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
					assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]







"""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()):
										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,
					)


