


from ..utils import is_flax_available, is_torch_available


if is_torch_available():
				from .autoencoder_kl import AutoencoderKL
				from .controlnet import ControlNetModel
				from .dual_transformer_ad import DualTransformeraDModel
				from .modeling_utils import ModelMixin
				from .prior_transformer import PriorTransformer
				from .ta_film_transformer import TaFilmDecoder
				from .transformer_ad import TransformeraDModel
				from .unet_ad import UNetaDModel
				from .unet_ad import UNetaDModel
				from .unet_ad_condition import UNetaDConditionModel
				from .unet_ad_condition import UNetaDConditionModel
				from .vq_model import VQModel

if is_flax_available():
				from .controlnet_flax import FlaxControlNetModel
				from .unet_ad_condition_flax import FlaxUNetaDConditionModel
				from .vae_flax import FlaxAutoencoderKL








def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE = 1000   ):
      '''simple docstring'''







      return sum(2 * a * ((a - 1) // 2) for a in range(3		,				n + 1   )   )


if __name__ == "__main__":
      print(solution())





