

from typing import List, Optional, Tuple, Union

import torch

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



class 					lowercase		( _UpperCamelCase      ):



 '''simple docstring'''


 __SCREAMING_SNAKE_CASE      							=       42
 __SCREAMING_SNAKE_CASE      							=       42




 def __init__(self , __a , __a				)				->      Union[str, Any]:






  """simple docstring"""





  super().__init__()

  UpperCAmelCase__           =       PNDMScheduler.from_config(scheduler.config				)

  self.register_modules(unet=__a , scheduler=__a				)




 @torch.no_grad()
 def __call__(self , __a = 1 , __a = 50 , __a = None , __a = "pil" , __a = True , **__a , )				->      Union[ImagePipelineOutput, Tuple]:






  """simple docstring"""





  UpperCAmelCase__           =       randn_tensor(
      (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size) , generator=__a , device=self.device , )

  self.scheduler.set_timesteps(__a				)
  for t in self.progress_bar(self.scheduler.timesteps				):
   UpperCAmelCase__           =       self.unet(__a , __a				).sample

   UpperCAmelCase__           =       self.scheduler.step(__a , __a , __a				).prev_sample

  UpperCAmelCase__           =       (image / 2 + 0.5).clamp(0 , 1				)
  UpperCAmelCase__           =       image.cpu().permute(0 , 2 , 3 , 1				).numpy()
  if output_type == "pil":
   UpperCAmelCase__           =       self.numpy_to_pil(__a				)

  if not return_dict:
   return (image,)

  return ImagePipelineOutput(images=__a				)






def 		UpperCamelCase_(    snake_case__:						int     ) ->				int:
 if not isinstance(snake_case__						,					snake_case__     ):
  UpperCAmelCase__           =       f"Input value of [number={number}] must be an integer"
  raise TypeError(snake_case__     )
 if number < 1:
  raise ValueError('Input must be a positive integer'     )
 return number * (2 * number - 1)


if __name__ == "__main__":
 import doctest

 doctest.testmod()



