




class   A:



 '''simple docstring'''


 def __init__(    self :  List[str]						,							A_ :  Dict  )       ->     Dict:

       """simple docstring"""






       lowerCamelCase_							=   len(lowerCamelCase__  )
       lowerCamelCase_							=   [0] * len_array

       if len_array > 0:
             lowerCamelCase_							=   array[0]

       for i in range(1						,							lowerCamelCase__  ):
             lowerCamelCase_							=   self.prefix_sum[i - 1] + array[i]

 def     a__			(    self :  Tuple						,							A_ :  Any						,							A_ :  List[str]  )       ->     List[str]:

       """simple docstring"""






       if start == 0:
             return self.prefix_sum[end]

       return self.prefix_sum[end] - self.prefix_sum[start - 1]





 def     a__			(    self :  Any						,							A_ :  Any  )       ->     int:

       """simple docstring"""






       lowerCamelCase_							=   {0}
       for sum_item in self.prefix_sum:
             if sum_item - target_sum in sums:
                   return True

             sums.add(lowerCamelCase__  )

       return False


if __name__ == "__main__":
      import doctest

      doctest.testmod()









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



