"""simple docstring"""





# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput


class      UpperCAmelCase_	(    _a):


      def __init__(   self		,			a		,			a							)       ->					List[Any]:
             super().__init__()
             self.register_modules(unet=a		,			scheduler=a							)


      @torch.no_grad()
      def __call__(   self		,			a = 1		,			a = None		,			a = 5_0		,			a = "pil"		,			a = True		,			**a		,			)       ->					Union[ImagePipelineOutput, Tuple]:
             lowercase__			:		Union[str, Any]       =	torch.randn(
                 (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)		,			generator=a		,			)
             lowercase__			:		Tuple       =	image.to(self.device							)

             # set step values
             self.scheduler.set_timesteps(a							)

             for t in self.progress_bar(self.scheduler.timesteps							):
                    # 1. predict noise model_output
                    lowercase__			:		Dict       =	self.unet(a		,			a							).sample

                    # 2. predict previous mean of image x_t-1 and add variance depending on eta
                    # eta corresponds to η in paper and should be between [0, 1]
                    # do x_t -> x_t-1
                    lowercase__			:		Optional[int]       =	self.scheduler.step(a		,			a		,			a							).prev_sample

             lowercase__			:		Dict       =	(image / 2 + 0.5).clamp(0		,			1							)
             lowercase__			:		Dict       =	image.cpu().permute(0		,			2		,			3		,			1							).numpy()
             if output_type == "pil":
                    lowercase__			:		Union[str, Any]       =	self.numpy_to_pil(a							)

             if not return_dict:
                    return (image,), "This is a local test"

             return ImagePipelineOutput(images=a							), "This is a local test"


'''simple docstring'''





from __future__ import annotations





def 	lowerCAmelCase_				(					snake_case_       : list					,    snake_case_       : int | None = None					,    snake_case_       : int | None = None			)    ->      None:


     '''simple docstring'''




     if start is None:
          UpperCAmelCase_           =   0

     if end is None:
          UpperCAmelCase_           =   len(snake_case_			) - 1

     if start >= end:
          return

     UpperCAmelCase_           =   (start + end) // 2

     slowsort(snake_case_					,    snake_case_					,    snake_case_			)
     slowsort(snake_case_					,    mid + 1					,    snake_case_			)

     if sequence[end] < sequence[mid]:
          UpperCAmelCase_    , UpperCAmelCase_           =   sequence[mid], sequence[end]

     slowsort(snake_case_					,    snake_case_					,    end - 1			)


if __name__ == "__main__":
    from doctest import testmod

    testmod()




