


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,
  )





def      a	(							SCREAMING_SNAKE_CASE_      :		int							,			SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





       if a < 0 or b < 0:
              raise ValueError('''the value of both inputs must be positive'''       )
       UpperCamelCase    :	int   	=		str(bin(SCREAMING_SNAKE_CASE_       )       )[2:]  # remove the leading "0b"
       UpperCamelCase    :	List[str]   	=		str(bin(SCREAMING_SNAKE_CASE_       )       )[2:]
       UpperCamelCase    :	Tuple   	=		max(len(SCREAMING_SNAKE_CASE_       )							,			len(SCREAMING_SNAKE_CASE_       )       )
       return "0b" + "".join(
           str(int('''1''' in (char_a, char_b)       )       )
           for char_a, char_b in zip(a_binary.zfill(SCREAMING_SNAKE_CASE_       )							,			b_binary.zfill(SCREAMING_SNAKE_CASE_       )       )       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()

