
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





import random

from .binary_exp_mod import bin_exp_mod






def   lowerCamelCase__							(					a		,		a=10_00      )      ->   Optional[int]:
   if n < 2:
      return False

   if n % 2 == 0:
      return n == 2

   # this means n is odd
   _A:  List[Any]					=       n - 1
   _A:  Dict					=       0
   while d % 2 == 0:
      d /= 2
      exp += 1

   # n - 1=d*(2**exp)
   _A:  List[str]					=       0
   while count < prec:
      _A:  Optional[int]					=       random.randint(2		,		n - 1      )
      _A:  Union[str, Any]					=       bin_exp_mod(a		,		a		,		a      )
      if b != 1:
         _A:  Optional[Any]					=       True
         for _ in range(a      ):
            if b == n - 1:
               _A:  int					=       False
               break
            _A:  Optional[Any]					=       b * b
            b %= n
         if flag:
            return False
         count += 1
   return True


if __name__ == "__main__":
   UpperCAmelCase__		:     Dict     			=      abs(int(input('Enter bound : ').strip()))
   print('Here\'s the list of primes:')
   print(', '.join(str(i) for i in range(n + 1) if is_prime_big(i)))



