


"""simple docstring"""


from ..utils import DummyObject, requires_backends



class   _a      (      metaclass=SCREAMING_SNAKE_CASE_ ):
    a_    :				List[Any]             =    ['transformers', 'torch', 'note_seq']
    def __init__( self							:					List[Any]							,					*SCREAMING_SNAKE_CASE__							:					Tuple							,					**SCREAMING_SNAKE_CASE__							:					List[Any]				):
          requires_backends(self							,					['transformers', 'torch', 'note_seq']				)
    @classmethod
    def      _UpperCamelCase       ( cls							:					str							,					*SCREAMING_SNAKE_CASE__							:					Union[str, Any]							,					**SCREAMING_SNAKE_CASE__							:					Tuple				):
          requires_backends(cls							,					['transformers', 'torch', 'note_seq']				)


    @classmethod
    def      _UpperCamelCase       ( cls							:					Optional[int]							,					*SCREAMING_SNAKE_CASE__							:					int							,					**SCREAMING_SNAKE_CASE__							:					int				):
          requires_backends(cls							,					['transformers', 'torch', 'note_seq']				)







"""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,
   )



