





from collections.abc import Sequence






def    _A	(   lowerCamelCase				,			lowerCamelCase ):
   return sum(c * (x**i) for i, c in enumerate(lowerCamelCase ) )






def    _A	(   lowerCamelCase				,			lowerCamelCase ):
   a__						:    Tuple   		=	0.0
   for coeff in reversed(lowerCamelCase ):
      a__						:    List[Any]   		=	result * x + coeff
   return result


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    (0.0, 0.0, 5.0, 9.3, 7.0)
  SCREAMING_SNAKE_CASE__							:      int         =    10.0
  print(evaluate_poly(poly, x))
  print(horner(poly, x))








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

