'''simple docstring'''




# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   def __init__(self       ,				_a       ,				_a				)    ->     int:
        super().__init__()
        self.register_modules(unet=_a       ,				scheduler=_a				)





   @torch.no_grad()
   def __call__(self       ,				_a = 1       ,				_a = None       ,				_a = 50       ,				_a = "pil"       ,				_a = True       ,				**_a       ,				)    ->     Union[ImagePipelineOutput, Tuple]:
        lowercase_					:       List[str]     				=					torch.randn(
            (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)       ,				generator=_a       ,				)
        lowercase_					:       Union[str, Any]     				=					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_					:       Any     				=					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[Any]     				=					self.scheduler.step(_a       ,				_a       ,				_a				).prev_sample

        lowercase_					:       List[Any]     				=					(image / 2 + 0.5).clamp(0       ,				1				)
        lowercase_					:       List[str]     				=					image.cpu().permute(0       ,				2       ,				3       ,				1				).numpy()
        if output_type == "pil":
             lowercase_					:       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'''




def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[Any]     				=					len(SCREAMING_SNAKE_CASE_							)
     for _ in range(SCREAMING_SNAKE_CASE_							):
          for i in range(_ % 2  ,       arr_size - 1  ,       2							):
               if arr[i + 1] < arr[i]:
                    lowercase_				,lowercase_					:       Optional[Any]     				=					arr[i + 1], arr[i]

     return arr


if __name__ == "__main__":
 _A								=   list(range(1_0, 0, -1))
 print(F"""Original: {arr}. Sorted: {odd_even_transposition(arr)}""")




