"""simple docstring"""


from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput






class    a__    (   _a	):
   snake_case_							=      42
   snake_case_							=      42


   def __init__(     self,				_UpperCAmelCase,				_UpperCAmelCase  ):
        '''simple docstring'''



        super().__init__()
        self.register_modules(unet=_UpperCAmelCase,				scheduler=_UpperCAmelCase  )


   @torch.no_grad()
   def __call__(     self,				_UpperCAmelCase = 1,				_UpperCAmelCase = 2000,				_UpperCAmelCase = None,				_UpperCAmelCase = "pil",				_UpperCAmelCase = True,				**_UpperCAmelCase,				):
        '''simple docstring'''



        lowercase__				 =							self.unet.config.sample_size
        lowercase__				 =							(batch_size, 3, img_size, img_size)

        lowercase__				 =							self.unet

        lowercase__				 =							randn_tensor(_UpperCAmelCase,				generator=_UpperCAmelCase  ) * self.scheduler.init_noise_sigma
        lowercase__				 =							sample.to(self.device  )

        self.scheduler.set_timesteps(_UpperCAmelCase  )
        self.scheduler.set_sigmas(_UpperCAmelCase  )

        for i, t in enumerate(self.progress_bar(self.scheduler.timesteps  )  ):
             lowercase__				 =							self.scheduler.sigmas[i] * torch.ones(shape[0],				device=self.device  )

             # correction step
             for _ in range(self.scheduler.config.correct_steps  ):
                  lowercase__				 =							self.unet(_UpperCAmelCase,				_UpperCAmelCase  ).sample
                  lowercase__				 =							self.scheduler.step_correct(_UpperCAmelCase,				_UpperCAmelCase,				generator=_UpperCAmelCase  ).prev_sample

             # prediction step
             lowercase__				 =							model(_UpperCAmelCase,				_UpperCAmelCase  ).sample
             lowercase__				 =							self.scheduler.step_pred(_UpperCAmelCase,				_UpperCAmelCase,				_UpperCAmelCase,				generator=_UpperCAmelCase  )

             lowercase__ ,						lowercase__				 =							output.prev_sample, output.prev_sample_mean

        lowercase__				 =							sample_mean.clamp(0,				1  )
        lowercase__				 =							sample.cpu().permute(0,				2,				3,				1  ).numpy()
        if output_type == "pil":
             lowercase__				 =							self.numpy_to_pil(_UpperCAmelCase  )

        if not return_dict:
             return (sample,)

        return ImagePipelineOutput(images=_UpperCAmelCase  )





"""simple docstring"""


from __future__ import annotations

import math







def 					__a   (		A      ):






     '''simple docstring'''



     if 1 < number < 4:
          # 2 and 3 are primes
          return True
     elif number < 2 or number % 2 == 0 or number % 3 == 0:
          # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
          return False

     # All primes number are in format of 6k +/- 1
     for i in range(5    ,				int(math.sqrt(A      ) + 1      )    ,				6      ):
          if number % i == 0 or number % (i + 2) == 0:
               return False
     return True


lowerCAmelCase_:					Optional[Any]     =					[num for num in range(3, 1_0_0_0_0_1, 2) if not is_prime(num)]







def 					__a   (		A      ):






     '''simple docstring'''



     if not isinstance(A    ,				A      ):
          raise ValueError("n must be an integer"      )
     if n <= 0:
          raise ValueError("n must be >= 0"      )

     lowercase__				 =							[]
     for num in range(len(A      )      ):
          lowercase__				 =							0
          while 2 * i * i <= odd_composites[num]:
               lowercase__				 =							odd_composites[num] - 2 * i * i
               if is_prime(A      ):
                    break
               i += 1
          else:
               list_nums.append(odd_composites[num]      )
               if len(A      ) == n:
                    return list_nums

     return []







def 					__a   (		):






     '''simple docstring'''



     return compute_nums(1      )[0]


if __name__ == "__main__":
 print(F'{solution() = }')




