




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


try:
       if not (is_transformers_available() and is_torch_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
       from .multicontrolnet import MultiControlNetModel
       from .pipeline_controlnet import StableDiffusionControlNetPipeline
       from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
       from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
       from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline













from __future__ import annotations

from math import pi





def      _UpperCamelCase  (a__ :float ,      a__ :float ,      a__ :float							):






							"""simple docstring"""





							if (inductance, frequency, reactance).count(0							) != 1:
														raise ValueError("""One and only one argument must be 0"""							)
							if inductance < 0:
														raise ValueError("""Inductance cannot be negative"""							)
							if frequency < 0:
														raise ValueError("""Frequency cannot be negative"""							)
							if reactance < 0:
														raise ValueError("""Inductive reactance cannot be negative"""							)
							if inductance == 0:
														return {"inductance": reactance / (2 * pi * frequency)}
							elif frequency == 0:
														return {"frequency": reactance / (2 * pi * inductance)}
							elif reactance == 0:
														return {"reactance": 2 * pi * frequency * inductance}
							else:
														raise ValueError("""Exactly one argument must be 0"""							)


if __name__ == "__main__":
					import doctest

					doctest.testmod()




