





'''simple docstring'''






from typing import List, Optional, Tuple, Union

import torch

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




class 					UpperCAmelCase	(     snake_case_  ):
      _lowercase:     UNetaDModel
      _lowercase:     KarrasVeScheduler




      def __init__(     self     :					str     ,     __snake_case     :					UNetaDModel     ,     __snake_case     :					KarrasVeScheduler    )							-> Any:
            super().__init__()
            self.register_modules(unet=__snake_case     ,     scheduler=__snake_case    )




      @torch.no_grad()
      def __call__(     self     :					int     ,     __snake_case     :					int = 1     ,     __snake_case     :					int = 50     ,     __snake_case     :					Optional[Union[torch.Generator, List[torch.Generator]]] = None     ,     __snake_case     :					Optional[str] = "pil"     ,     __snake_case     :					bool = True     ,     **__snake_case     :					Any     ,     )							-> Union[Tuple, ImagePipelineOutput]:
            _lowerCAmelCase					=				self.unet.config.sample_size
            _lowerCAmelCase					=				(batch_size, 3, img_size, img_size)

            _lowerCAmelCase					=				self.unet

            # sample x_0 ~ N(0, sigma_0^2 * I)
            _lowerCAmelCase					=				randn_tensor(__snake_case     ,     generator=__snake_case     ,     device=self.device    ) * self.scheduler.init_noise_sigma

            self.scheduler.set_timesteps(__snake_case    )

            for t in self.progress_bar(self.scheduler.timesteps    ):
                  # here sigma_t == t_i from the paper
                  _lowerCAmelCase					=				self.scheduler.schedule[t]
                  _lowerCAmelCase					=				self.scheduler.schedule[t - 1] if t > 0 else 0

                  # 1. Select temporarily increased noise level sigma_hat
                  # 2. Add new noise to move from sample_i to sample_hat
                  _lowerCAmelCase	,				_lowerCAmelCase					=				self.scheduler.add_noise_to_input(__snake_case     ,     __snake_case     ,     generator=__snake_case    )

                  # 3. Predict the noise residual given the noise magnitude `sigma_hat`
                  # The model inputs and output are adjusted by following eq. (213) in [1].
                  _lowerCAmelCase					=				(sigma_hat / 2) * model((sample_hat + 1) / 2     ,     sigma_hat / 2    ).sample

                  # 4. Evaluate dx/dt at sigma_hat
                  # 5. Take Euler step from sigma to sigma_prev
                  _lowerCAmelCase					=				self.scheduler.step(__snake_case     ,     __snake_case     ,     __snake_case     ,     __snake_case    )

                  if sigma_prev != 0:
                        # 6. Apply 2nd order correction
                        # The model inputs and output are adjusted by following eq. (213) in [1].
                        _lowerCAmelCase					=				(sigma_prev / 2) * model((step_output.prev_sample + 1) / 2     ,     sigma_prev / 2    ).sample
                        _lowerCAmelCase					=				self.scheduler.step_correct(
                            __snake_case     ,     __snake_case     ,     __snake_case     ,     __snake_case     ,     step_output.prev_sample     ,     step_output["""derivative"""]     ,     )
                  _lowerCAmelCase					=				step_output.prev_sample

            _lowerCAmelCase					=				(sample / 2 + 0.5).clamp(0     ,     1    )
            _lowerCAmelCase					=				sample.cpu().permute(0     ,     2     ,     3     ,     1    ).numpy()
            if output_type == "pil":
                  _lowerCAmelCase					=				self.numpy_to_pil(__snake_case    )

            if not return_dict:
                  return (image,)

            return ImagePipelineOutput(images=__snake_case    )













'''simple docstring'''






def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      if divisor % 5 == 0 or divisor % 2 == 0:
            return 0
      _lowerCAmelCase					=				1
      _lowerCAmelCase					=				1
      while repunit:
            _lowerCAmelCase					=				(10 * repunit + 1) % divisor
            repunit_index += 1
      return repunit_index
def   UpperCamelCase__ (						lowerCAmelCase = 1_00_00_00    ):





      """simple docstring"""


      _lowerCAmelCase					=				limit - 1
      if divisor % 2 == 0:
            divisor += 1
      while least_divisible_repunit(lowerCAmelCase    ) <= limit:
            divisor += 2
      return divisor


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






